Class ActiveLearningConfig.Builder (2.4.0)

Version 2.4.0

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public static final class ActiveLearningConfig.Builder extends GeneratedMessageV3.Builder<ActiveLearningConfig.Builder> implements ActiveLearningConfigOrBuilder

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

Protobuf type google.cloud.aiplatform.v1.ActiveLearningConfig

Inheritance

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

Implements

ActiveLearningConfigOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ActiveLearningConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public ActiveLearningConfig build()

Returns

Type	Description
ActiveLearningConfig

buildPartial()

public ActiveLearningConfig buildPartial()

Returns

Type	Description
ActiveLearningConfig

clear()

public ActiveLearningConfig.Builder clear()

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearField(Descriptors.FieldDescriptor field)

public ActiveLearningConfig.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearHumanLabelingBudget()

public ActiveLearningConfig.Builder clearHumanLabelingBudget()

Returns

Type	Description
ActiveLearningConfig.Builder

clearMaxDataItemCount()

public ActiveLearningConfig.Builder clearMaxDataItemCount()

Max number of human labeled DataItems.

int64 max_data_item_count = 1;

Returns

Type	Description
ActiveLearningConfig.Builder	This builder for chaining.

clearMaxDataItemPercentage()

public ActiveLearningConfig.Builder clearMaxDataItemPercentage()

Max percent of total DataItems for human labeling.

int32 max_data_item_percentage = 2;

Returns

Type	Description
ActiveLearningConfig.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public ActiveLearningConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearSampleConfig()

public ActiveLearningConfig.Builder clearSampleConfig()

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Returns

Type	Description
ActiveLearningConfig.Builder

clearTrainingConfig()

public ActiveLearningConfig.Builder clearTrainingConfig()

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Returns

Type	Description
ActiveLearningConfig.Builder

clone()

public ActiveLearningConfig.Builder clone()

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getDefaultInstanceForType()

public ActiveLearningConfig getDefaultInstanceForType()

Returns

Type	Description
ActiveLearningConfig

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getHumanLabelingBudgetCase()

public ActiveLearningConfig.HumanLabelingBudgetCase getHumanLabelingBudgetCase()

Returns

Type	Description
ActiveLearningConfig.HumanLabelingBudgetCase

getMaxDataItemCount()

public long getMaxDataItemCount()

Max number of human labeled DataItems.

int64 max_data_item_count = 1;

Returns

Type	Description
long	The maxDataItemCount.

getMaxDataItemPercentage()

public int getMaxDataItemPercentage()

Max percent of total DataItems for human labeling.

int32 max_data_item_percentage = 2;

Returns

Type	Description
int	The maxDataItemPercentage.

getSampleConfig()

public SampleConfig getSampleConfig()

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Returns

Type	Description
SampleConfig	The sampleConfig.

getSampleConfigBuilder()

public SampleConfig.Builder getSampleConfigBuilder()

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Returns

Type	Description
SampleConfig.Builder

getSampleConfigOrBuilder()

public SampleConfigOrBuilder getSampleConfigOrBuilder()

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Returns

Type	Description
SampleConfigOrBuilder

getTrainingConfig()

public TrainingConfig getTrainingConfig()

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Returns

Type	Description
TrainingConfig	The trainingConfig.

getTrainingConfigBuilder()

public TrainingConfig.Builder getTrainingConfigBuilder()

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Returns

Type	Description
TrainingConfig.Builder

getTrainingConfigOrBuilder()

public TrainingConfigOrBuilder getTrainingConfigOrBuilder()

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Returns

Type	Description
TrainingConfigOrBuilder

hasMaxDataItemCount()

public boolean hasMaxDataItemCount()

Max number of human labeled DataItems.

int64 max_data_item_count = 1;

Returns

Type	Description
boolean	Whether the maxDataItemCount field is set.

hasMaxDataItemPercentage()

public boolean hasMaxDataItemPercentage()

Max percent of total DataItems for human labeling.

int32 max_data_item_percentage = 2;

Returns

Type	Description
boolean	Whether the maxDataItemPercentage field is set.

hasSampleConfig()

public boolean hasSampleConfig()

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Returns

Type	Description
boolean	Whether the sampleConfig field is set.

hasTrainingConfig()

public boolean hasTrainingConfig()

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Returns

Type	Description
boolean	Whether the trainingConfig field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(ActiveLearningConfig other)

public ActiveLearningConfig.Builder mergeFrom(ActiveLearningConfig other)

Parameter

Name	Description
other	ActiveLearningConfig

Returns

Type	Description
ActiveLearningConfig.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ActiveLearningConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public ActiveLearningConfig.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeSampleConfig(SampleConfig value)

public ActiveLearningConfig.Builder mergeSampleConfig(SampleConfig value)

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Parameter

Name	Description
value	SampleConfig

Returns

Type	Description
ActiveLearningConfig.Builder

mergeTrainingConfig(TrainingConfig value)

public ActiveLearningConfig.Builder mergeTrainingConfig(TrainingConfig value)

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Parameter

Name	Description
value	TrainingConfig

Returns

Type	Description
ActiveLearningConfig.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ActiveLearningConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

setField(Descriptors.FieldDescriptor field, Object value)

public ActiveLearningConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setMaxDataItemCount(long value)

public ActiveLearningConfig.Builder setMaxDataItemCount(long value)

Max number of human labeled DataItems.

int64 max_data_item_count = 1;

Parameter

Name	Description
value	long The maxDataItemCount to set.

Returns

Type	Description
ActiveLearningConfig.Builder	This builder for chaining.

setMaxDataItemPercentage(int value)

public ActiveLearningConfig.Builder setMaxDataItemPercentage(int value)

Max percent of total DataItems for human labeling.

int32 max_data_item_percentage = 2;

Parameter

Name	Description
value	int The maxDataItemPercentage to set.

Returns

Type	Description
ActiveLearningConfig.Builder	This builder for chaining.

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

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

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setSampleConfig(SampleConfig value)

public ActiveLearningConfig.Builder setSampleConfig(SampleConfig value)

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Parameter

Name	Description
value	SampleConfig

Returns

Type	Description
ActiveLearningConfig.Builder

setSampleConfig(SampleConfig.Builder builderForValue)

public ActiveLearningConfig.Builder setSampleConfig(SampleConfig.Builder builderForValue)

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

.google.cloud.aiplatform.v1.SampleConfig sample_config = 3;

Parameter

Name	Description
builderForValue	SampleConfig.Builder

Returns

Type	Description
ActiveLearningConfig.Builder

setTrainingConfig(TrainingConfig value)

public ActiveLearningConfig.Builder setTrainingConfig(TrainingConfig value)

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Parameter

Name	Description
value	TrainingConfig

Returns

Type	Description
ActiveLearningConfig.Builder

setTrainingConfig(TrainingConfig.Builder builderForValue)

public ActiveLearningConfig.Builder setTrainingConfig(TrainingConfig.Builder builderForValue)

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

.google.cloud.aiplatform.v1.TrainingConfig training_config = 4;

Parameter

Name	Description
builderForValue	TrainingConfig.Builder

Returns

Type	Description
ActiveLearningConfig.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final ActiveLearningConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ActiveLearningConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)