Class FeatureStatsAndAnomaly.Builder (3.55.0)

Version 3.55.0

• 3.56.0 (latest)
• 3.55.0
• 3.54.0
• 3.53.0
• 3.52.0
• 3.50.0
• 3.49.0
• 3.48.0
• 3.47.0
• 3.46.0
• 3.45.0
• 3.44.0
• 3.43.0
• 3.42.0
• 3.41.0
• 3.40.0
• 3.38.0
• 3.37.0
• 3.36.0
• 3.35.0
• 3.34.0
• 3.33.0
• 3.32.0
• 3.31.0
• 3.30.0
• 3.29.0
• 3.28.0
• 3.25.0
• 3.24.0
• 3.23.0
• 3.22.0
• 3.21.0
• 3.20.0
• 3.19.0
• 3.18.0
• 3.17.0
• 3.16.0
• 3.15.0
• 3.14.0
• 3.13.0
• 3.12.0
• 3.11.0
• 3.10.0
• 3.9.0
• 3.8.0
• 3.7.0
• 3.6.0
• 3.5.0
• 3.4.2
• 3.3.0
• 3.2.0
• 3.0.0
• 2.9.8
• 2.8.9
• 2.7.4
• 2.5.3
• 2.4.0

public static final class FeatureStatsAndAnomaly.Builder extends GeneratedMessageV3.Builder<FeatureStatsAndAnomaly.Builder> implements FeatureStatsAndAnomalyOrBuilder

Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift.

Protobuf type google.cloud.aiplatform.v1beta1.FeatureStatsAndAnomaly

Inheritance

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

Implements

FeatureStatsAndAnomalyOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

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.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

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)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

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

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

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

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)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

build()

public FeatureStatsAndAnomaly build()

Returns
Type	Description
FeatureStatsAndAnomaly

buildPartial()

public FeatureStatsAndAnomaly buildPartial()

Returns
Type	Description
FeatureStatsAndAnomaly

clear()

public FeatureStatsAndAnomaly.Builder clear()

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearDistributionDeviation()

public FeatureStatsAndAnomaly.Builder clearDistributionDeviation()

Deviation from the current stats to baseline stats.

1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 3;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

clearDriftDetected()

public FeatureStatsAndAnomaly.Builder clearDriftDetected()

If set to true, indicates current stats is detected as and comparing with baseline stats.

bool drift_detected = 5;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

clearDriftDetectionThreshold()

public FeatureStatsAndAnomaly.Builder clearDriftDetectionThreshold()

This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold

double drift_detection_threshold = 4;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

clearFeatureId()

public FeatureStatsAndAnomaly.Builder clearFeatureId()

Feature Id.

string feature_id = 1;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

clearFeatureMonitorId()

public FeatureStatsAndAnomaly.Builder clearFeatureMonitorId()

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

clearFeatureMonitorJobId()

public FeatureStatsAndAnomaly.Builder clearFeatureMonitorJobId()

The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.

int64 feature_monitor_job_id = 7;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

clearFeatureStats()

public FeatureStatsAndAnomaly.Builder clearFeatureStats()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

clearField(Descriptors.FieldDescriptor field)

public FeatureStatsAndAnomaly.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

clearOneof(Descriptors.OneofDescriptor oneof)

public FeatureStatsAndAnomaly.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

clearStatsTime()

public FeatureStatsAndAnomaly.Builder clearStatsTime()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

clone()

public FeatureStatsAndAnomaly.Builder clone()

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getDefaultInstanceForType()

public FeatureStatsAndAnomaly getDefaultInstanceForType()

Returns
Type	Description
FeatureStatsAndAnomaly

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDistributionDeviation()

public double getDistributionDeviation()

Deviation from the current stats to baseline stats.

1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 3;

Returns
Type	Description
double	The distributionDeviation.

getDriftDetected()

public boolean getDriftDetected()

If set to true, indicates current stats is detected as and comparing with baseline stats.

bool drift_detected = 5;

Returns
Type	Description
boolean	The driftDetected.

getDriftDetectionThreshold()

public double getDriftDetectionThreshold()

This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold

double drift_detection_threshold = 4;

Returns
Type	Description
double	The driftDetectionThreshold.

getFeatureId()

public String getFeatureId()

Feature Id.

string feature_id = 1;

Returns
Type	Description
String	The featureId.

getFeatureIdBytes()

public ByteString getFeatureIdBytes()

Feature Id.

string feature_id = 1;

Returns
Type	Description
ByteString	The bytes for featureId.

getFeatureMonitorId()

public String getFeatureMonitorId()

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Returns
Type	Description
String	The featureMonitorId.

getFeatureMonitorIdBytes()

public ByteString getFeatureMonitorIdBytes()

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Returns
Type	Description
ByteString	The bytes for featureMonitorId.

getFeatureMonitorJobId()

public long getFeatureMonitorJobId()

The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.

int64 feature_monitor_job_id = 7;

Returns
Type	Description
long	The featureMonitorJobId.

getFeatureStats()

public Value getFeatureStats()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type	Description
Value	The featureStats.

getFeatureStatsBuilder()

public Value.Builder getFeatureStatsBuilder()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type	Description
Builder

getFeatureStatsOrBuilder()

public ValueOrBuilder getFeatureStatsOrBuilder()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type	Description
ValueOrBuilder

getStatsTime()

public Timestamp getStatsTime()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type	Description
Timestamp	The statsTime.

getStatsTimeBuilder()

public Timestamp.Builder getStatsTimeBuilder()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type	Description
Builder

getStatsTimeOrBuilder()

public TimestampOrBuilder getStatsTimeOrBuilder()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type	Description
TimestampOrBuilder

hasFeatureStats()

public boolean hasFeatureStats()

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Returns
Type	Description
boolean	Whether the featureStats field is set.

hasStatsTime()

public boolean hasStatsTime()

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Returns
Type	Description
boolean	Whether the statsTime 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()

mergeFeatureStats(Value value)

public FeatureStatsAndAnomaly.Builder mergeFeatureStats(Value value)

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Parameter
Name	Description
value	Value

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

mergeFrom(FeatureStatsAndAnomaly other)

public FeatureStatsAndAnomaly.Builder mergeFrom(FeatureStatsAndAnomaly other)

Parameter
Name	Description
other	FeatureStatsAndAnomaly

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public FeatureStatsAndAnomaly.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

mergeStatsTime(Timestamp value)

public FeatureStatsAndAnomaly.Builder mergeStatsTime(Timestamp value)

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final FeatureStatsAndAnomaly.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

setDistributionDeviation(double value)

public FeatureStatsAndAnomaly.Builder setDistributionDeviation(double value)

Deviation from the current stats to baseline stats.

1. For categorical feature, the distribution distance is calculated by L-inifinity norm.
2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence.

double distribution_deviation = 3;

Parameter
Name	Description
value	double The distributionDeviation to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setDriftDetected(boolean value)

public FeatureStatsAndAnomaly.Builder setDriftDetected(boolean value)

If set to true, indicates current stats is detected as and comparing with baseline stats.

bool drift_detected = 5;

Parameter
Name	Description
value	boolean The driftDetected to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setDriftDetectionThreshold(double value)

public FeatureStatsAndAnomaly.Builder setDriftDetectionThreshold(double value)

This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold

double drift_detection_threshold = 4;

Parameter
Name	Description
value	double The driftDetectionThreshold to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setFeatureId(String value)

public FeatureStatsAndAnomaly.Builder setFeatureId(String value)

Feature Id.

string feature_id = 1;

Parameter
Name	Description
value	String The featureId to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setFeatureIdBytes(ByteString value)

public FeatureStatsAndAnomaly.Builder setFeatureIdBytes(ByteString value)

Feature Id.

string feature_id = 1;

Parameter
Name	Description
value	ByteString The bytes for featureId to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setFeatureMonitorId(String value)

public FeatureStatsAndAnomaly.Builder setFeatureMonitorId(String value)

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Parameter
Name	Description
value	String The featureMonitorId to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setFeatureMonitorIdBytes(ByteString value)

public FeatureStatsAndAnomaly.Builder setFeatureMonitorIdBytes(ByteString value)

The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to.

string feature_monitor_id = 8;

Parameter
Name	Description
value	ByteString The bytes for featureMonitorId to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setFeatureMonitorJobId(long value)

public FeatureStatsAndAnomaly.Builder setFeatureMonitorJobId(long value)

The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly.

int64 feature_monitor_job_id = 7;

Parameter
Name	Description
value	long The featureMonitorJobId to set.

Returns
Type	Description
FeatureStatsAndAnomaly.Builder	This builder for chaining.

setFeatureStats(Value value)

public FeatureStatsAndAnomaly.Builder setFeatureStats(Value value)

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Parameter
Name	Description
value	Value

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

setFeatureStats(Value.Builder builderForValue)

public FeatureStatsAndAnomaly.Builder setFeatureStats(Value.Builder builderForValue)

Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics.

.google.protobuf.Value feature_stats = 2;

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

setField(Descriptors.FieldDescriptor field, Object value)

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

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

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

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

Parameters
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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

setStatsTime(Timestamp value)

public FeatureStatsAndAnomaly.Builder setStatsTime(Timestamp value)

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Parameter
Name	Description
value	Timestamp

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

setStatsTime(Timestamp.Builder builderForValue)

public FeatureStatsAndAnomaly.Builder setStatsTime(Timestamp.Builder builderForValue)

The timestamp we take snapshot for feature values to generate stats.

.google.protobuf.Timestamp stats_time = 6;

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

setUnknownFields(UnknownFieldSet unknownFields)

public final FeatureStatsAndAnomaly.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
FeatureStatsAndAnomaly.Builder

Overrides

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