Class ExplanationMetadata.InputMetadata.Visualization.Builder (2.4.0)

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public static final class ExplanationMetadata.InputMetadata.Visualization.Builder extends GeneratedMessageV3.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder> implements ExplanationMetadata.InputMetadata.VisualizationOrBuilder

Visualization configurations for image explanation.

Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ExplanationMetadata.InputMetadata.Visualization.Builder

Implements

ExplanationMetadata.InputMetadata.VisualizationOrBuilder

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 ExplanationMetadata.InputMetadata.Visualization.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

build()

public ExplanationMetadata.InputMetadata.Visualization build()

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization

buildPartial()

public ExplanationMetadata.InputMetadata.Visualization buildPartial()

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization

clear()

public ExplanationMetadata.InputMetadata.Visualization.Builder clear()

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearClipPercentLowerbound()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearClipPercentLowerbound()

Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.

float clip_percent_lowerbound = 5;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

clearClipPercentUpperbound()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearClipPercentUpperbound()

Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.

float clip_percent_upperbound = 4;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

clearColorMap()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearColorMap()

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ExplanationMetadata.InputMetadata.Visualization.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

clearOneof(Descriptors.OneofDescriptor oneof)

public ExplanationMetadata.InputMetadata.Visualization.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

clearOverlayType()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearOverlayType()

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

clearPolarity()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearPolarity()

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

clearType()

public ExplanationMetadata.InputMetadata.Visualization.Builder clearType()

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

clone()

public ExplanationMetadata.InputMetadata.Visualization.Builder clone()

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getClipPercentLowerbound()

public float getClipPercentLowerbound()

Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.

float clip_percent_lowerbound = 5;

Returns

Type	Description
float	The clipPercentLowerbound.

getClipPercentUpperbound()

public float getClipPercentUpperbound()

Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.

float clip_percent_upperbound = 4;

Returns

Type	Description
float	The clipPercentUpperbound.

getColorMap()

public ExplanationMetadata.InputMetadata.Visualization.ColorMap getColorMap()

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.ColorMap	The colorMap.

getColorMapValue()

public int getColorMapValue()

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Returns

Type	Description
int	The enum numeric value on the wire for colorMap.

getDefaultInstanceForType()

public ExplanationMetadata.InputMetadata.Visualization getDefaultInstanceForType()

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization

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()

getOverlayType()

public ExplanationMetadata.InputMetadata.Visualization.OverlayType getOverlayType()

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.OverlayType	The overlayType.

getOverlayTypeValue()

public int getOverlayTypeValue()

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Returns

Type	Description
int	The enum numeric value on the wire for overlayType.

getPolarity()

public ExplanationMetadata.InputMetadata.Visualization.Polarity getPolarity()

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Polarity	The polarity.

getPolarityValue()

public int getPolarityValue()

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Returns

Type	Description
int	The enum numeric value on the wire for polarity.

getType()

public ExplanationMetadata.InputMetadata.Visualization.Type getType()

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Type	The type.

getTypeValue()

public int getTypeValue()

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Returns

Type	Description
int	The enum numeric value on the wire for type.

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(ExplanationMetadata.InputMetadata.Visualization other)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(ExplanationMetadata.InputMetadata.Visualization other)

Parameter

Name	Description
other	ExplanationMetadata.InputMetadata.Visualization

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public ExplanationMetadata.InputMetadata.Visualization.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.InputMetadata.Visualization.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

setClipPercentLowerbound(float value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setClipPercentLowerbound(float value)

Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62.

float clip_percent_lowerbound = 5;

Parameter

Name	Description
value	float The clipPercentLowerbound to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setClipPercentUpperbound(float value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setClipPercentUpperbound(float value)

Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9.

float clip_percent_upperbound = 4;

Parameter

Name	Description
value	float The clipPercentUpperbound to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setColorMap(ExplanationMetadata.InputMetadata.Visualization.ColorMap value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setColorMap(ExplanationMetadata.InputMetadata.Visualization.ColorMap value)

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Parameter

Name	Description
value	ExplanationMetadata.InputMetadata.Visualization.ColorMap The colorMap to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setColorMapValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setColorMapValue(int value)

The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;

Parameter

Name	Description
value	int The enum numeric value on the wire for colorMap to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

setOverlayType(ExplanationMetadata.InputMetadata.Visualization.OverlayType value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setOverlayType(ExplanationMetadata.InputMetadata.Visualization.OverlayType value)

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Parameter

Name	Description
value	ExplanationMetadata.InputMetadata.Visualization.OverlayType The overlayType to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setOverlayTypeValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setOverlayTypeValue(int value)

How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;

Parameter

Name	Description
value	int The enum numeric value on the wire for overlayType to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setPolarity(ExplanationMetadata.InputMetadata.Visualization.Polarity value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setPolarity(ExplanationMetadata.InputMetadata.Visualization.Polarity value)

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Parameter

Name	Description
value	ExplanationMetadata.InputMetadata.Visualization.Polarity The polarity to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setPolarityValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setPolarityValue(int value)

Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;

Parameter

Name	Description
value	int The enum numeric value on the wire for polarity to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

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

public ExplanationMetadata.InputMetadata.Visualization.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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

setType(ExplanationMetadata.InputMetadata.Visualization.Type value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setType(ExplanationMetadata.InputMetadata.Visualization.Type value)

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Parameter

Name	Description
value	ExplanationMetadata.InputMetadata.Visualization.Type The type to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setTypeValue(int value)

public ExplanationMetadata.InputMetadata.Visualization.Builder setTypeValue(int value)

Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;

Parameter

Name	Description
value	int The enum numeric value on the wire for type to set.

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder	This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.InputMetadata.Visualization.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
ExplanationMetadata.InputMetadata.Visualization.Builder

Overrides

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