public static final class Model.Builder extends com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder> implements ModelOrBuilder
A trained machine learning Model.Protobuf type
google.cloud.aiplatform.v1beta1.Model| Modifier and Type | Method and Description |
|---|---|
Model.Builder |
addAllDeployedModels(Iterable<? extends DeployedModelRef> values)
Output only.
|
Model.Builder |
addAllSupportedDeploymentResourcesTypes(Iterable<? extends Model.DeploymentResourcesType> values)
Output only.
|
Model.Builder |
addAllSupportedDeploymentResourcesTypesValue(Iterable<Integer> values)
Output only.
|
Model.Builder |
addAllSupportedExportFormats(Iterable<? extends Model.ExportFormat> values)
Output only.
|
Model.Builder |
addAllSupportedInputStorageFormats(Iterable<String> values)
Output only.
|
Model.Builder |
addAllSupportedOutputStorageFormats(Iterable<String> values)
Output only.
|
Model.Builder |
addAllVersionAliases(Iterable<String> values)
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
Model.Builder |
addDeployedModels(DeployedModelRef.Builder builderForValue)
Output only.
|
Model.Builder |
addDeployedModels(DeployedModelRef value)
Output only.
|
Model.Builder |
addDeployedModels(int index,
DeployedModelRef.Builder builderForValue)
Output only.
|
Model.Builder |
addDeployedModels(int index,
DeployedModelRef value)
Output only.
|
DeployedModelRef.Builder |
addDeployedModelsBuilder()
Output only.
|
DeployedModelRef.Builder |
addDeployedModelsBuilder(int index)
Output only.
|
Model.Builder |
addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
Object value) |
Model.Builder |
addSupportedDeploymentResourcesTypes(Model.DeploymentResourcesType value)
Output only.
|
Model.Builder |
addSupportedDeploymentResourcesTypesValue(int value)
Output only.
|
Model.Builder |
addSupportedExportFormats(int index,
Model.ExportFormat.Builder builderForValue)
Output only.
|
Model.Builder |
addSupportedExportFormats(int index,
Model.ExportFormat value)
Output only.
|
Model.Builder |
addSupportedExportFormats(Model.ExportFormat.Builder builderForValue)
Output only.
|
Model.Builder |
addSupportedExportFormats(Model.ExportFormat value)
Output only.
|
Model.ExportFormat.Builder |
addSupportedExportFormatsBuilder()
Output only.
|
Model.ExportFormat.Builder |
addSupportedExportFormatsBuilder(int index)
Output only.
|
Model.Builder |
addSupportedInputStorageFormats(String value)
Output only.
|
Model.Builder |
addSupportedInputStorageFormatsBytes(com.google.protobuf.ByteString value)
Output only.
|
Model.Builder |
addSupportedOutputStorageFormats(String value)
Output only.
|
Model.Builder |
addSupportedOutputStorageFormatsBytes(com.google.protobuf.ByteString value)
Output only.
|
Model.Builder |
addVersionAliases(String value)
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
Model.Builder |
addVersionAliasesBytes(com.google.protobuf.ByteString value)
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
Model |
build() |
Model |
buildPartial() |
Model.Builder |
clear() |
Model.Builder |
clearArtifactUri()
Immutable.
|
Model.Builder |
clearContainerSpec()
Input only.
|
Model.Builder |
clearCreateTime()
Output only.
|
Model.Builder |
clearDeployedModels()
Output only.
|
Model.Builder |
clearDescription()
The description of the Model.
|
Model.Builder |
clearDisplayName()
Required.
|
Model.Builder |
clearEncryptionSpec()
Customer-managed encryption key spec for a Model.
|
Model.Builder |
clearEtag()
Used to perform consistent read-modify-write updates.
|
Model.Builder |
clearExplanationSpec()
The default explanation specification for this Model.
|
Model.Builder |
clearField(com.google.protobuf.Descriptors.FieldDescriptor field) |
Model.Builder |
clearLabels() |
Model.Builder |
clearMetadata()
Immutable.
|
Model.Builder |
clearMetadataSchemaUri()
Immutable.
|
Model.Builder |
clearName()
The resource name of the Model.
|
Model.Builder |
clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) |
Model.Builder |
clearPredictSchemata()
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
Model.Builder |
clearSupportedDeploymentResourcesTypes()
Output only.
|
Model.Builder |
clearSupportedExportFormats()
Output only.
|
Model.Builder |
clearSupportedInputStorageFormats()
Output only.
|
Model.Builder |
clearSupportedOutputStorageFormats()
Output only.
|
Model.Builder |
clearTrainingPipeline()
Output only.
|
Model.Builder |
clearUpdateTime()
Output only.
|
Model.Builder |
clearVersionAliases()
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
Model.Builder |
clearVersionCreateTime()
Output only.
|
Model.Builder |
clearVersionDescription()
The description of this version.
|
Model.Builder |
clearVersionId()
Output only.
|
Model.Builder |
clearVersionUpdateTime()
Output only.
|
Model.Builder |
clone() |
boolean |
containsLabels(String key)
The labels with user-defined metadata to organize your Models.
|
String |
getArtifactUri()
Immutable.
|
com.google.protobuf.ByteString |
getArtifactUriBytes()
Immutable.
|
ModelContainerSpec |
getContainerSpec()
Input only.
|
ModelContainerSpec.Builder |
getContainerSpecBuilder()
Input only.
|
ModelContainerSpecOrBuilder |
getContainerSpecOrBuilder()
Input only.
|
com.google.protobuf.Timestamp |
getCreateTime()
Output only.
|
com.google.protobuf.Timestamp.Builder |
getCreateTimeBuilder()
Output only.
|
com.google.protobuf.TimestampOrBuilder |
getCreateTimeOrBuilder()
Output only.
|
Model |
getDefaultInstanceForType() |
DeployedModelRef |
getDeployedModels(int index)
Output only.
|
DeployedModelRef.Builder |
getDeployedModelsBuilder(int index)
Output only.
|
List<DeployedModelRef.Builder> |
getDeployedModelsBuilderList()
Output only.
|
int |
getDeployedModelsCount()
Output only.
|
List<DeployedModelRef> |
getDeployedModelsList()
Output only.
|
DeployedModelRefOrBuilder |
getDeployedModelsOrBuilder(int index)
Output only.
|
List<? extends DeployedModelRefOrBuilder> |
getDeployedModelsOrBuilderList()
Output only.
|
String |
getDescription()
The description of the Model.
|
com.google.protobuf.ByteString |
getDescriptionBytes()
The description of the Model.
|
static com.google.protobuf.Descriptors.Descriptor |
getDescriptor() |
com.google.protobuf.Descriptors.Descriptor |
getDescriptorForType() |
String |
getDisplayName()
Required.
|
com.google.protobuf.ByteString |
getDisplayNameBytes()
Required.
|
EncryptionSpec |
getEncryptionSpec()
Customer-managed encryption key spec for a Model.
|
EncryptionSpec.Builder |
getEncryptionSpecBuilder()
Customer-managed encryption key spec for a Model.
|
EncryptionSpecOrBuilder |
getEncryptionSpecOrBuilder()
Customer-managed encryption key spec for a Model.
|
String |
getEtag()
Used to perform consistent read-modify-write updates.
|
com.google.protobuf.ByteString |
getEtagBytes()
Used to perform consistent read-modify-write updates.
|
ExplanationSpec |
getExplanationSpec()
The default explanation specification for this Model.
|
ExplanationSpec.Builder |
getExplanationSpecBuilder()
The default explanation specification for this Model.
|
ExplanationSpecOrBuilder |
getExplanationSpecOrBuilder()
The default explanation specification for this Model.
|
Map<String,String> |
getLabels()
Deprecated.
|
int |
getLabelsCount()
The labels with user-defined metadata to organize your Models.
|
Map<String,String> |
getLabelsMap()
The labels with user-defined metadata to organize your Models.
|
String |
getLabelsOrDefault(String key,
String defaultValue)
The labels with user-defined metadata to organize your Models.
|
String |
getLabelsOrThrow(String key)
The labels with user-defined metadata to organize your Models.
|
com.google.protobuf.Value |
getMetadata()
Immutable.
|
com.google.protobuf.Value.Builder |
getMetadataBuilder()
Immutable.
|
com.google.protobuf.ValueOrBuilder |
getMetadataOrBuilder()
Immutable.
|
String |
getMetadataSchemaUri()
Immutable.
|
com.google.protobuf.ByteString |
getMetadataSchemaUriBytes()
Immutable.
|
Map<String,String> |
getMutableLabels()
Deprecated.
|
String |
getName()
The resource name of the Model.
|
com.google.protobuf.ByteString |
getNameBytes()
The resource name of the Model.
|
PredictSchemata |
getPredictSchemata()
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
PredictSchemata.Builder |
getPredictSchemataBuilder()
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
PredictSchemataOrBuilder |
getPredictSchemataOrBuilder()
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
Model.DeploymentResourcesType |
getSupportedDeploymentResourcesTypes(int index)
Output only.
|
int |
getSupportedDeploymentResourcesTypesCount()
Output only.
|
List<Model.DeploymentResourcesType> |
getSupportedDeploymentResourcesTypesList()
Output only.
|
int |
getSupportedDeploymentResourcesTypesValue(int index)
Output only.
|
List<Integer> |
getSupportedDeploymentResourcesTypesValueList()
Output only.
|
Model.ExportFormat |
getSupportedExportFormats(int index)
Output only.
|
Model.ExportFormat.Builder |
getSupportedExportFormatsBuilder(int index)
Output only.
|
List<Model.ExportFormat.Builder> |
getSupportedExportFormatsBuilderList()
Output only.
|
int |
getSupportedExportFormatsCount()
Output only.
|
List<Model.ExportFormat> |
getSupportedExportFormatsList()
Output only.
|
Model.ExportFormatOrBuilder |
getSupportedExportFormatsOrBuilder(int index)
Output only.
|
List<? extends Model.ExportFormatOrBuilder> |
getSupportedExportFormatsOrBuilderList()
Output only.
|
String |
getSupportedInputStorageFormats(int index)
Output only.
|
com.google.protobuf.ByteString |
getSupportedInputStorageFormatsBytes(int index)
Output only.
|
int |
getSupportedInputStorageFormatsCount()
Output only.
|
com.google.protobuf.ProtocolStringList |
getSupportedInputStorageFormatsList()
Output only.
|
String |
getSupportedOutputStorageFormats(int index)
Output only.
|
com.google.protobuf.ByteString |
getSupportedOutputStorageFormatsBytes(int index)
Output only.
|
int |
getSupportedOutputStorageFormatsCount()
Output only.
|
com.google.protobuf.ProtocolStringList |
getSupportedOutputStorageFormatsList()
Output only.
|
String |
getTrainingPipeline()
Output only.
|
com.google.protobuf.ByteString |
getTrainingPipelineBytes()
Output only.
|
com.google.protobuf.Timestamp |
getUpdateTime()
Output only.
|
com.google.protobuf.Timestamp.Builder |
getUpdateTimeBuilder()
Output only.
|
com.google.protobuf.TimestampOrBuilder |
getUpdateTimeOrBuilder()
Output only.
|
String |
getVersionAliases(int index)
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
com.google.protobuf.ByteString |
getVersionAliasesBytes(int index)
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
int |
getVersionAliasesCount()
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
com.google.protobuf.ProtocolStringList |
getVersionAliasesList()
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
com.google.protobuf.Timestamp |
getVersionCreateTime()
Output only.
|
com.google.protobuf.Timestamp.Builder |
getVersionCreateTimeBuilder()
Output only.
|
com.google.protobuf.TimestampOrBuilder |
getVersionCreateTimeOrBuilder()
Output only.
|
String |
getVersionDescription()
The description of this version.
|
com.google.protobuf.ByteString |
getVersionDescriptionBytes()
The description of this version.
|
String |
getVersionId()
Output only.
|
com.google.protobuf.ByteString |
getVersionIdBytes()
Output only.
|
com.google.protobuf.Timestamp |
getVersionUpdateTime()
Output only.
|
com.google.protobuf.Timestamp.Builder |
getVersionUpdateTimeBuilder()
Output only.
|
com.google.protobuf.TimestampOrBuilder |
getVersionUpdateTimeOrBuilder()
Output only.
|
boolean |
hasContainerSpec()
Input only.
|
boolean |
hasCreateTime()
Output only.
|
boolean |
hasEncryptionSpec()
Customer-managed encryption key spec for a Model.
|
boolean |
hasExplanationSpec()
The default explanation specification for this Model.
|
boolean |
hasMetadata()
Immutable.
|
boolean |
hasPredictSchemata()
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
boolean |
hasUpdateTime()
Output only.
|
boolean |
hasVersionCreateTime()
Output only.
|
boolean |
hasVersionUpdateTime()
Output only.
|
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable |
internalGetFieldAccessorTable() |
protected com.google.protobuf.MapField |
internalGetMapField(int number) |
protected com.google.protobuf.MapField |
internalGetMutableMapField(int number) |
boolean |
isInitialized() |
Model.Builder |
mergeContainerSpec(ModelContainerSpec value)
Input only.
|
Model.Builder |
mergeCreateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
mergeEncryptionSpec(EncryptionSpec value)
Customer-managed encryption key spec for a Model.
|
Model.Builder |
mergeExplanationSpec(ExplanationSpec value)
The default explanation specification for this Model.
|
Model.Builder |
mergeFrom(com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry) |
Model.Builder |
mergeFrom(com.google.protobuf.Message other) |
Model.Builder |
mergeFrom(Model other) |
Model.Builder |
mergeMetadata(com.google.protobuf.Value value)
Immutable.
|
Model.Builder |
mergePredictSchemata(PredictSchemata value)
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
Model.Builder |
mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) |
Model.Builder |
mergeUpdateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
mergeVersionCreateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
mergeVersionUpdateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
putAllLabels(Map<String,String> values)
The labels with user-defined metadata to organize your Models.
|
Model.Builder |
putLabels(String key,
String value)
The labels with user-defined metadata to organize your Models.
|
Model.Builder |
removeDeployedModels(int index)
Output only.
|
Model.Builder |
removeLabels(String key)
The labels with user-defined metadata to organize your Models.
|
Model.Builder |
removeSupportedExportFormats(int index)
Output only.
|
Model.Builder |
setArtifactUri(String value)
Immutable.
|
Model.Builder |
setArtifactUriBytes(com.google.protobuf.ByteString value)
Immutable.
|
Model.Builder |
setContainerSpec(ModelContainerSpec.Builder builderForValue)
Input only.
|
Model.Builder |
setContainerSpec(ModelContainerSpec value)
Input only.
|
Model.Builder |
setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only.
|
Model.Builder |
setCreateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
setDeployedModels(int index,
DeployedModelRef.Builder builderForValue)
Output only.
|
Model.Builder |
setDeployedModels(int index,
DeployedModelRef value)
Output only.
|
Model.Builder |
setDescription(String value)
The description of the Model.
|
Model.Builder |
setDescriptionBytes(com.google.protobuf.ByteString value)
The description of the Model.
|
Model.Builder |
setDisplayName(String value)
Required.
|
Model.Builder |
setDisplayNameBytes(com.google.protobuf.ByteString value)
Required.
|
Model.Builder |
setEncryptionSpec(EncryptionSpec.Builder builderForValue)
Customer-managed encryption key spec for a Model.
|
Model.Builder |
setEncryptionSpec(EncryptionSpec value)
Customer-managed encryption key spec for a Model.
|
Model.Builder |
setEtag(String value)
Used to perform consistent read-modify-write updates.
|
Model.Builder |
setEtagBytes(com.google.protobuf.ByteString value)
Used to perform consistent read-modify-write updates.
|
Model.Builder |
setExplanationSpec(ExplanationSpec.Builder builderForValue)
The default explanation specification for this Model.
|
Model.Builder |
setExplanationSpec(ExplanationSpec value)
The default explanation specification for this Model.
|
Model.Builder |
setField(com.google.protobuf.Descriptors.FieldDescriptor field,
Object value) |
Model.Builder |
setMetadata(com.google.protobuf.Value.Builder builderForValue)
Immutable.
|
Model.Builder |
setMetadata(com.google.protobuf.Value value)
Immutable.
|
Model.Builder |
setMetadataSchemaUri(String value)
Immutable.
|
Model.Builder |
setMetadataSchemaUriBytes(com.google.protobuf.ByteString value)
Immutable.
|
Model.Builder |
setName(String value)
The resource name of the Model.
|
Model.Builder |
setNameBytes(com.google.protobuf.ByteString value)
The resource name of the Model.
|
Model.Builder |
setPredictSchemata(PredictSchemata.Builder builderForValue)
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
Model.Builder |
setPredictSchemata(PredictSchemata value)
The schemata that describe formats of the Model's predictions and
explanations as given and returned via
[PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
|
Model.Builder |
setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
int index,
Object value) |
Model.Builder |
setSupportedDeploymentResourcesTypes(int index,
Model.DeploymentResourcesType value)
Output only.
|
Model.Builder |
setSupportedDeploymentResourcesTypesValue(int index,
int value)
Output only.
|
Model.Builder |
setSupportedExportFormats(int index,
Model.ExportFormat.Builder builderForValue)
Output only.
|
Model.Builder |
setSupportedExportFormats(int index,
Model.ExportFormat value)
Output only.
|
Model.Builder |
setSupportedInputStorageFormats(int index,
String value)
Output only.
|
Model.Builder |
setSupportedOutputStorageFormats(int index,
String value)
Output only.
|
Model.Builder |
setTrainingPipeline(String value)
Output only.
|
Model.Builder |
setTrainingPipelineBytes(com.google.protobuf.ByteString value)
Output only.
|
Model.Builder |
setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) |
Model.Builder |
setUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only.
|
Model.Builder |
setUpdateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
setVersionAliases(int index,
String value)
User provided version aliases so that a model version can be referenced via
alias (i.e.
|
Model.Builder |
setVersionCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only.
|
Model.Builder |
setVersionCreateTime(com.google.protobuf.Timestamp value)
Output only.
|
Model.Builder |
setVersionDescription(String value)
The description of this version.
|
Model.Builder |
setVersionDescriptionBytes(com.google.protobuf.ByteString value)
The description of this version.
|
Model.Builder |
setVersionId(String value)
Output only.
|
Model.Builder |
setVersionIdBytes(com.google.protobuf.ByteString value)
Output only.
|
Model.Builder |
setVersionUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only.
|
Model.Builder |
setVersionUpdateTime(com.google.protobuf.Timestamp value)
Output only.
|
getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, isClean, markClean, newBuilderForField, onBuilt, onChanged, setUnknownFieldsProto3findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringaddAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageExceptionequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitfindInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneofpublic static final com.google.protobuf.Descriptors.Descriptor getDescriptor()
protected com.google.protobuf.MapField internalGetMapField(int number)
internalGetMapField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>protected com.google.protobuf.MapField internalGetMutableMapField(int number)
internalGetMutableMapField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder clear()
clear in interface com.google.protobuf.Message.Builderclear in interface com.google.protobuf.MessageLite.Builderclear in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
getDescriptorForType in interface com.google.protobuf.Message.BuildergetDescriptorForType in interface com.google.protobuf.MessageOrBuildergetDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model getDefaultInstanceForType()
getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuildergetDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilderpublic Model build()
build in interface com.google.protobuf.Message.Builderbuild in interface com.google.protobuf.MessageLite.Builderpublic Model buildPartial()
buildPartial in interface com.google.protobuf.Message.BuilderbuildPartial in interface com.google.protobuf.MessageLite.Builderpublic Model.Builder clone()
clone in interface com.google.protobuf.Message.Builderclone in interface com.google.protobuf.MessageLite.Builderclone in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
setField in interface com.google.protobuf.Message.BuildersetField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
clearField in interface com.google.protobuf.Message.BuilderclearField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
clearOneof in interface com.google.protobuf.Message.BuilderclearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
setRepeatedField in interface com.google.protobuf.Message.BuildersetRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
addRepeatedField in interface com.google.protobuf.Message.BuilderaddRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder mergeFrom(com.google.protobuf.Message other)
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<Model.Builder>public Model.Builder mergeFrom(Model other)
public final boolean isInitialized()
isInitialized in interface com.google.protobuf.MessageLiteOrBuilderisInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public Model.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
mergeFrom in interface com.google.protobuf.Message.BuildermergeFrom in interface com.google.protobuf.MessageLite.BuildermergeFrom in class com.google.protobuf.AbstractMessage.Builder<Model.Builder>IOExceptionpublic String getName()
The resource name of the Model.
string name = 1;getName in interface ModelOrBuilderpublic com.google.protobuf.ByteString getNameBytes()
The resource name of the Model.
string name = 1;getNameBytes in interface ModelOrBuilderpublic Model.Builder setName(String value)
The resource name of the Model.
string name = 1;value - The name to set.public Model.Builder clearName()
The resource name of the Model.
string name = 1;public Model.Builder setNameBytes(com.google.protobuf.ByteString value)
The resource name of the Model.
string name = 1;value - The bytes for name to set.public String getVersionId()
Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.
string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
getVersionId in interface ModelOrBuilderpublic com.google.protobuf.ByteString getVersionIdBytes()
Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.
string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
getVersionIdBytes in interface ModelOrBuilderpublic Model.Builder setVersionId(String value)
Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.
string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
value - The versionId to set.public Model.Builder clearVersionId()
Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.
string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setVersionIdBytes(com.google.protobuf.ByteString value)
Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation.
string version_id = 28 [(.google.api.field_behavior) = IMMUTABLE, (.google.api.field_behavior) = OUTPUT_ONLY];
value - The bytes for versionId to set.public com.google.protobuf.ProtocolStringList getVersionAliasesList()
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;getVersionAliasesList in interface ModelOrBuilderpublic int getVersionAliasesCount()
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;getVersionAliasesCount in interface ModelOrBuilderpublic String getVersionAliases(int index)
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;getVersionAliases in interface ModelOrBuilderindex - The index of the element to return.public com.google.protobuf.ByteString getVersionAliasesBytes(int index)
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;getVersionAliasesBytes in interface ModelOrBuilderindex - The index of the value to return.public Model.Builder setVersionAliases(int index, String value)
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;index - The index to set the value at.value - The versionAliases to set.public Model.Builder addVersionAliases(String value)
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;value - The versionAliases to add.public Model.Builder addAllVersionAliases(Iterable<String> values)
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;values - The versionAliases to add.public Model.Builder clearVersionAliases()
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;public Model.Builder addVersionAliasesBytes(com.google.protobuf.ByteString value)
User provided version aliases so that a model version can be referenced via
alias (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_alias}
instead of auto-generated version id (i.e.
projects/{project}/locations/{location}/models/{model_id}@{version_id}).
The format is [a-z][a-zA-Z0-9-]{0,126}[a-z0-9] to distinguish from
version_id. A default version alias will be created for the first version
of the model, and there must be exactly one default version alias for a
model.
repeated string version_aliases = 29;value - The bytes of the versionAliases to add.public boolean hasVersionCreateTime()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
hasVersionCreateTime in interface ModelOrBuilderpublic com.google.protobuf.Timestamp getVersionCreateTime()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
getVersionCreateTime in interface ModelOrBuilderpublic Model.Builder setVersionCreateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setVersionCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder mergeVersionCreateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder clearVersionCreateTime()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.Timestamp.Builder getVersionCreateTimeBuilder()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.TimestampOrBuilder getVersionCreateTimeOrBuilder()
Output only. Timestamp when this version was created.
.google.protobuf.Timestamp version_create_time = 31 [(.google.api.field_behavior) = OUTPUT_ONLY];
getVersionCreateTimeOrBuilder in interface ModelOrBuilderpublic boolean hasVersionUpdateTime()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
hasVersionUpdateTime in interface ModelOrBuilderpublic com.google.protobuf.Timestamp getVersionUpdateTime()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
getVersionUpdateTime in interface ModelOrBuilderpublic Model.Builder setVersionUpdateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setVersionUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder mergeVersionUpdateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder clearVersionUpdateTime()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.Timestamp.Builder getVersionUpdateTimeBuilder()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.TimestampOrBuilder getVersionUpdateTimeOrBuilder()
Output only. Timestamp when this version was most recently updated.
.google.protobuf.Timestamp version_update_time = 32 [(.google.api.field_behavior) = OUTPUT_ONLY];
getVersionUpdateTimeOrBuilder in interface ModelOrBuilderpublic String getDisplayName()
Required. The display name of the Model. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];getDisplayName in interface ModelOrBuilderpublic com.google.protobuf.ByteString getDisplayNameBytes()
Required. The display name of the Model. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];getDisplayNameBytes in interface ModelOrBuilderpublic Model.Builder setDisplayName(String value)
Required. The display name of the Model. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];value - The displayName to set.public Model.Builder clearDisplayName()
Required. The display name of the Model. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];public Model.Builder setDisplayNameBytes(com.google.protobuf.ByteString value)
Required. The display name of the Model. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
string display_name = 2 [(.google.api.field_behavior) = REQUIRED];value - The bytes for displayName to set.public String getDescription()
The description of the Model.
string description = 3;getDescription in interface ModelOrBuilderpublic com.google.protobuf.ByteString getDescriptionBytes()
The description of the Model.
string description = 3;getDescriptionBytes in interface ModelOrBuilderpublic Model.Builder setDescription(String value)
The description of the Model.
string description = 3;value - The description to set.public Model.Builder clearDescription()
The description of the Model.
string description = 3;public Model.Builder setDescriptionBytes(com.google.protobuf.ByteString value)
The description of the Model.
string description = 3;value - The bytes for description to set.public String getVersionDescription()
The description of this version.
string version_description = 30;getVersionDescription in interface ModelOrBuilderpublic com.google.protobuf.ByteString getVersionDescriptionBytes()
The description of this version.
string version_description = 30;getVersionDescriptionBytes in interface ModelOrBuilderpublic Model.Builder setVersionDescription(String value)
The description of this version.
string version_description = 30;value - The versionDescription to set.public Model.Builder clearVersionDescription()
The description of this version.
string version_description = 30;public Model.Builder setVersionDescriptionBytes(com.google.protobuf.ByteString value)
The description of this version.
string version_description = 30;value - The bytes for versionDescription to set.public boolean hasPredictSchemata()
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;hasPredictSchemata in interface ModelOrBuilderpublic PredictSchemata getPredictSchemata()
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;getPredictSchemata in interface ModelOrBuilderpublic Model.Builder setPredictSchemata(PredictSchemata value)
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;public Model.Builder setPredictSchemata(PredictSchemata.Builder builderForValue)
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;public Model.Builder mergePredictSchemata(PredictSchemata value)
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;public Model.Builder clearPredictSchemata()
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;public PredictSchemata.Builder getPredictSchemataBuilder()
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;public PredictSchemataOrBuilder getPredictSchemataOrBuilder()
The schemata that describe formats of the Model's predictions and explanations as given and returned via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] and [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
.google.cloud.aiplatform.v1beta1.PredictSchemata predict_schemata = 4;getPredictSchemataOrBuilder in interface ModelOrBuilderpublic String getMetadataSchemaUri()
Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];getMetadataSchemaUri in interface ModelOrBuilderpublic com.google.protobuf.ByteString getMetadataSchemaUriBytes()
Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];getMetadataSchemaUriBytes in interface ModelOrBuilderpublic Model.Builder setMetadataSchemaUri(String value)
Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];value - The metadataSchemaUri to set.public Model.Builder clearMetadataSchemaUri()
Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];public Model.Builder setMetadataSchemaUriBytes(com.google.protobuf.ByteString value)
Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access.
string metadata_schema_uri = 5 [(.google.api.field_behavior) = IMMUTABLE];value - The bytes for metadataSchemaUri to set.public boolean hasMetadata()
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];hasMetadata in interface ModelOrBuilderpublic com.google.protobuf.Value getMetadata()
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];getMetadata in interface ModelOrBuilderpublic Model.Builder setMetadata(com.google.protobuf.Value value)
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];public Model.Builder setMetadata(com.google.protobuf.Value.Builder builderForValue)
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];public Model.Builder mergeMetadata(com.google.protobuf.Value value)
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];public Model.Builder clearMetadata()
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];public com.google.protobuf.Value.Builder getMetadataBuilder()
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];public com.google.protobuf.ValueOrBuilder getMetadataOrBuilder()
Immutable. An additional information about the Model; the schema of the metadata can be found in [metadata_schema][google.cloud.aiplatform.v1beta1.Model.metadata_schema_uri]. Unset if the Model does not have any additional information.
.google.protobuf.Value metadata = 6 [(.google.api.field_behavior) = IMMUTABLE];getMetadataOrBuilder in interface ModelOrBuilderpublic List<Model.ExportFormat> getSupportedExportFormatsList()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedExportFormatsList in interface ModelOrBuilderpublic int getSupportedExportFormatsCount()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedExportFormatsCount in interface ModelOrBuilderpublic Model.ExportFormat getSupportedExportFormats(int index)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedExportFormats in interface ModelOrBuilderpublic Model.Builder setSupportedExportFormats(int index, Model.ExportFormat value)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setSupportedExportFormats(int index, Model.ExportFormat.Builder builderForValue)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addSupportedExportFormats(Model.ExportFormat value)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addSupportedExportFormats(int index, Model.ExportFormat value)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addSupportedExportFormats(Model.ExportFormat.Builder builderForValue)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addSupportedExportFormats(int index, Model.ExportFormat.Builder builderForValue)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addAllSupportedExportFormats(Iterable<? extends Model.ExportFormat> values)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder clearSupportedExportFormats()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder removeSupportedExportFormats(int index)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.ExportFormat.Builder getSupportedExportFormatsBuilder(int index)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.ExportFormatOrBuilder getSupportedExportFormatsOrBuilder(int index)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedExportFormatsOrBuilder in interface ModelOrBuilderpublic List<? extends Model.ExportFormatOrBuilder> getSupportedExportFormatsOrBuilderList()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedExportFormatsOrBuilderList in interface ModelOrBuilderpublic Model.ExportFormat.Builder addSupportedExportFormatsBuilder()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.ExportFormat.Builder addSupportedExportFormatsBuilder(int index)
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public List<Model.ExportFormat.Builder> getSupportedExportFormatsBuilderList()
Output only. The formats in which this Model may be exported. If empty, this Model is not available for export.
repeated .google.cloud.aiplatform.v1beta1.Model.ExportFormat supported_export_formats = 20 [(.google.api.field_behavior) = OUTPUT_ONLY];
public String getTrainingPipeline()
Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.
string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
getTrainingPipeline in interface ModelOrBuilderpublic com.google.protobuf.ByteString getTrainingPipelineBytes()
Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.
string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
getTrainingPipelineBytes in interface ModelOrBuilderpublic Model.Builder setTrainingPipeline(String value)
Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.
string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
value - The trainingPipeline to set.public Model.Builder clearTrainingPipeline()
Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.
string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
public Model.Builder setTrainingPipelineBytes(com.google.protobuf.ByteString value)
Output only. The resource name of the TrainingPipeline that uploaded this Model, if any.
string training_pipeline = 7 [(.google.api.field_behavior) = OUTPUT_ONLY, (.google.api.resource_reference) = { ... }
value - The bytes for trainingPipeline to set.public boolean hasContainerSpec()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
hasContainerSpec in interface ModelOrBuilderpublic ModelContainerSpec getContainerSpec()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
getContainerSpec in interface ModelOrBuilderpublic Model.Builder setContainerSpec(ModelContainerSpec value)
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
public Model.Builder setContainerSpec(ModelContainerSpec.Builder builderForValue)
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
public Model.Builder mergeContainerSpec(ModelContainerSpec value)
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
public Model.Builder clearContainerSpec()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
public ModelContainerSpec.Builder getContainerSpecBuilder()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
public ModelContainerSpecOrBuilder getContainerSpecOrBuilder()
Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel], and all binaries it contains are copied and stored internally by Vertex AI. Not present for AutoML Models.
.google.cloud.aiplatform.v1beta1.ModelContainerSpec container_spec = 9 [(.google.api.field_behavior) = INPUT_ONLY];
getContainerSpecOrBuilder in interface ModelOrBuilderpublic String getArtifactUri()
Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models.
string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];getArtifactUri in interface ModelOrBuilderpublic com.google.protobuf.ByteString getArtifactUriBytes()
Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models.
string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];getArtifactUriBytes in interface ModelOrBuilderpublic Model.Builder setArtifactUri(String value)
Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models.
string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];value - The artifactUri to set.public Model.Builder clearArtifactUri()
Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models.
string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];public Model.Builder setArtifactUriBytes(com.google.protobuf.ByteString value)
Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not present for AutoML Models.
string artifact_uri = 26 [(.google.api.field_behavior) = IMMUTABLE];value - The bytes for artifactUri to set.public List<Model.DeploymentResourcesType> getSupportedDeploymentResourcesTypesList()
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedDeploymentResourcesTypesList in interface ModelOrBuilderpublic int getSupportedDeploymentResourcesTypesCount()
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedDeploymentResourcesTypesCount in interface ModelOrBuilderpublic Model.DeploymentResourcesType getSupportedDeploymentResourcesTypes(int index)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedDeploymentResourcesTypes in interface ModelOrBuilderindex - The index of the element to return.public Model.Builder setSupportedDeploymentResourcesTypes(int index, Model.DeploymentResourcesType value)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
index - The index to set the value at.value - The supportedDeploymentResourcesTypes to set.public Model.Builder addSupportedDeploymentResourcesTypes(Model.DeploymentResourcesType value)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
value - The supportedDeploymentResourcesTypes to add.public Model.Builder addAllSupportedDeploymentResourcesTypes(Iterable<? extends Model.DeploymentResourcesType> values)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
values - The supportedDeploymentResourcesTypes to add.public Model.Builder clearSupportedDeploymentResourcesTypes()
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
public List<Integer> getSupportedDeploymentResourcesTypesValueList()
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedDeploymentResourcesTypesValueList in interface ModelOrBuilderpublic int getSupportedDeploymentResourcesTypesValue(int index)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedDeploymentResourcesTypesValue in interface ModelOrBuilderindex - The index of the value to return.public Model.Builder setSupportedDeploymentResourcesTypesValue(int index, int value)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
index - The index of the value to return.public Model.Builder addSupportedDeploymentResourcesTypesValue(int value)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
value - The enum numeric value on the wire for supportedDeploymentResourcesTypes to add.public Model.Builder addAllSupportedDeploymentResourcesTypesValue(Iterable<Integer> values)
Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the [Endpoint.deployed_models][google.cloud.aiplatform.v1beta1.Endpoint.deployed_models] object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and does not support online predictions ([PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain]). Such a Model can serve predictions by using a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob], if it has at least one entry each in [supported_input_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_input_storage_formats] and [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
repeated .google.cloud.aiplatform.v1beta1.Model.DeploymentResourcesType supported_deployment_resources_types = 10 [(.google.api.field_behavior) = OUTPUT_ONLY];
values - The enum numeric values on the wire for supportedDeploymentResourcesTypes to
add.public com.google.protobuf.ProtocolStringList getSupportedInputStorageFormatsList()
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedInputStorageFormatsList in interface ModelOrBuilderpublic int getSupportedInputStorageFormatsCount()
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedInputStorageFormatsCount in interface ModelOrBuilderpublic String getSupportedInputStorageFormats(int index)
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedInputStorageFormats in interface ModelOrBuilderindex - The index of the element to return.public com.google.protobuf.ByteString getSupportedInputStorageFormatsBytes(int index)
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedInputStorageFormatsBytes in interface ModelOrBuilderindex - The index of the value to return.public Model.Builder setSupportedInputStorageFormats(int index, String value)
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
index - The index to set the value at.value - The supportedInputStorageFormats to set.public Model.Builder addSupportedInputStorageFormats(String value)
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
value - The supportedInputStorageFormats to add.public Model.Builder addAllSupportedInputStorageFormats(Iterable<String> values)
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
values - The supportedInputStorageFormats to add.public Model.Builder clearSupportedInputStorageFormats()
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addSupportedInputStorageFormatsBytes(com.google.protobuf.ByteString value)
Output only. The formats this Model supports in [BatchPredictionJob.input_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.input_config]. If [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses [GcsSource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.gcs_source]. * `bigquery` Each instance is a single row in BigQuery. Uses [BigQuerySource][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig.bigquery_source]. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the [InputConfig][google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig] object. If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_input_storage_formats = 11 [(.google.api.field_behavior) = OUTPUT_ONLY];
value - The bytes of the supportedInputStorageFormats to add.public com.google.protobuf.ProtocolStringList getSupportedOutputStorageFormatsList()
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedOutputStorageFormatsList in interface ModelOrBuilderpublic int getSupportedOutputStorageFormatsCount()
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedOutputStorageFormatsCount in interface ModelOrBuilderpublic String getSupportedOutputStorageFormats(int index)
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedOutputStorageFormats in interface ModelOrBuilderindex - The index of the element to return.public com.google.protobuf.ByteString getSupportedOutputStorageFormatsBytes(int index)
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
getSupportedOutputStorageFormatsBytes in interface ModelOrBuilderindex - The index of the value to return.public Model.Builder setSupportedOutputStorageFormats(int index, String value)
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
index - The index to set the value at.value - The supportedOutputStorageFormats to set.public Model.Builder addSupportedOutputStorageFormats(String value)
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
value - The supportedOutputStorageFormats to add.public Model.Builder addAllSupportedOutputStorageFormats(Iterable<String> values)
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
values - The supportedOutputStorageFormats to add.public Model.Builder clearSupportedOutputStorageFormats()
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addSupportedOutputStorageFormatsBytes(com.google.protobuf.ByteString value)
Output only. The formats this Model supports in [BatchPredictionJob.output_config][google.cloud.aiplatform.v1beta1.BatchPredictionJob.output_config]. If both [PredictSchemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri] and [PredictSchemata.prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri] exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses [GcsDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.gcs_destination]. * `bigquery` Each prediction is a single row in a BigQuery table, uses [BigQueryDestination][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.bigquery_destination] . If this Model doesn't support any of these formats it means it cannot be used with a [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. However, if it has [supported_deployment_resources_types][google.cloud.aiplatform.v1beta1.Model.supported_deployment_resources_types], it could serve online predictions by using [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict] or [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
repeated string supported_output_storage_formats = 12 [(.google.api.field_behavior) = OUTPUT_ONLY];
value - The bytes of the supportedOutputStorageFormats to add.public boolean hasCreateTime()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
hasCreateTime in interface ModelOrBuilderpublic com.google.protobuf.Timestamp getCreateTime()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
getCreateTime in interface ModelOrBuilderpublic Model.Builder setCreateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder mergeCreateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder clearCreateTime()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
Output only. Timestamp when this Model was uploaded into Vertex AI.
.google.protobuf.Timestamp create_time = 13 [(.google.api.field_behavior) = OUTPUT_ONLY];
getCreateTimeOrBuilder in interface ModelOrBuilderpublic boolean hasUpdateTime()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
hasUpdateTime in interface ModelOrBuilderpublic com.google.protobuf.Timestamp getUpdateTime()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
getUpdateTime in interface ModelOrBuilderpublic Model.Builder setUpdateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setUpdateTime(com.google.protobuf.Timestamp.Builder builderForValue)
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder mergeUpdateTime(com.google.protobuf.Timestamp value)
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder clearUpdateTime()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.Timestamp.Builder getUpdateTimeBuilder()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
public com.google.protobuf.TimestampOrBuilder getUpdateTimeOrBuilder()
Output only. Timestamp when this Model was most recently updated.
.google.protobuf.Timestamp update_time = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
getUpdateTimeOrBuilder in interface ModelOrBuilderpublic List<DeployedModelRef> getDeployedModelsList()
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
getDeployedModelsList in interface ModelOrBuilderpublic int getDeployedModelsCount()
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
getDeployedModelsCount in interface ModelOrBuilderpublic DeployedModelRef getDeployedModels(int index)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
getDeployedModels in interface ModelOrBuilderpublic Model.Builder setDeployedModels(int index, DeployedModelRef value)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder setDeployedModels(int index, DeployedModelRef.Builder builderForValue)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addDeployedModels(DeployedModelRef value)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addDeployedModels(int index, DeployedModelRef value)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addDeployedModels(DeployedModelRef.Builder builderForValue)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addDeployedModels(int index, DeployedModelRef.Builder builderForValue)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder addAllDeployedModels(Iterable<? extends DeployedModelRef> values)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder clearDeployedModels()
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public Model.Builder removeDeployedModels(int index)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public DeployedModelRef.Builder getDeployedModelsBuilder(int index)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public DeployedModelRefOrBuilder getDeployedModelsOrBuilder(int index)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
getDeployedModelsOrBuilder in interface ModelOrBuilderpublic List<? extends DeployedModelRefOrBuilder> getDeployedModelsOrBuilderList()
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
getDeployedModelsOrBuilderList in interface ModelOrBuilderpublic DeployedModelRef.Builder addDeployedModelsBuilder()
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public DeployedModelRef.Builder addDeployedModelsBuilder(int index)
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public List<DeployedModelRef.Builder> getDeployedModelsBuilderList()
Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations.
repeated .google.cloud.aiplatform.v1beta1.DeployedModelRef deployed_models = 15 [(.google.api.field_behavior) = OUTPUT_ONLY];
public boolean hasExplanationSpec()
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;hasExplanationSpec in interface ModelOrBuilderpublic ExplanationSpec getExplanationSpec()
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;getExplanationSpec in interface ModelOrBuilderpublic Model.Builder setExplanationSpec(ExplanationSpec value)
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;public Model.Builder setExplanationSpec(ExplanationSpec.Builder builderForValue)
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;public Model.Builder mergeExplanationSpec(ExplanationSpec value)
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;public Model.Builder clearExplanationSpec()
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;public ExplanationSpec.Builder getExplanationSpecBuilder()
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;public ExplanationSpecOrBuilder getExplanationSpecOrBuilder()
The default explanation specification for this Model. The Model can be used for [requesting explanation][PredictionService.Explain] after being [deployed][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel] if it is populated. The Model can be used for [batch explanation][BatchPredictionJob.generate_explanation] if it is populated. All fields of the explanation_spec can be overridden by [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model], or [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob]. If the default explanation specification is not set for this Model, this Model can still be used for [requesting explanation][PredictionService.Explain] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] of [DeployModelRequest.deployed_model][google.cloud.aiplatform.v1beta1.DeployModelRequest.deployed_model] and for [batch explanation][BatchPredictionJob.generate_explanation] by setting [explanation_spec][google.cloud.aiplatform.v1beta1.BatchPredictionJob.explanation_spec] of [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 23;getExplanationSpecOrBuilder in interface ModelOrBuilderpublic String getEtag()
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;getEtag in interface ModelOrBuilderpublic com.google.protobuf.ByteString getEtagBytes()
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;getEtagBytes in interface ModelOrBuilderpublic Model.Builder setEtag(String value)
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;value - The etag to set.public Model.Builder clearEtag()
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;public Model.Builder setEtagBytes(com.google.protobuf.ByteString value)
Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
string etag = 16;value - The bytes for etag to set.public int getLabelsCount()
ModelOrBuilderThe labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;getLabelsCount in interface ModelOrBuilderpublic boolean containsLabels(String key)
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;containsLabels in interface ModelOrBuilder@Deprecated public Map<String,String> getLabels()
getLabelsMap() instead.getLabels in interface ModelOrBuilderpublic Map<String,String> getLabelsMap()
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;getLabelsMap in interface ModelOrBuilderpublic String getLabelsOrDefault(String key, String defaultValue)
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;getLabelsOrDefault in interface ModelOrBuilderpublic String getLabelsOrThrow(String key)
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;getLabelsOrThrow in interface ModelOrBuilderpublic Model.Builder clearLabels()
public Model.Builder removeLabels(String key)
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;@Deprecated public Map<String,String> getMutableLabels()
public Model.Builder putLabels(String key, String value)
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;public Model.Builder putAllLabels(Map<String,String> values)
The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.
map<string, string> labels = 17;public boolean hasEncryptionSpec()
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;hasEncryptionSpec in interface ModelOrBuilderpublic EncryptionSpec getEncryptionSpec()
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;getEncryptionSpec in interface ModelOrBuilderpublic Model.Builder setEncryptionSpec(EncryptionSpec value)
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;public Model.Builder setEncryptionSpec(EncryptionSpec.Builder builderForValue)
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;public Model.Builder mergeEncryptionSpec(EncryptionSpec value)
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;public Model.Builder clearEncryptionSpec()
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;public EncryptionSpec.Builder getEncryptionSpecBuilder()
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;public EncryptionSpecOrBuilder getEncryptionSpecOrBuilder()
Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key.
.google.cloud.aiplatform.v1beta1.EncryptionSpec encryption_spec = 24;getEncryptionSpecOrBuilder in interface ModelOrBuilderpublic final Model.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
setUnknownFields in interface com.google.protobuf.Message.BuildersetUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>public final Model.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
mergeUnknownFields in interface com.google.protobuf.Message.BuildermergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<Model.Builder>Copyright © 2022 Google LLC. All rights reserved.