com.google.cloud.aiplatform.v1beta1

Class ModelEvaluation.BiasConfig.Builder

java.lang.Object

com.google.protobuf.AbstractMessageLite.Builder

com.google.protobuf.AbstractMessage.Builder<BuilderT>

com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

com.google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig.Builder

All Implemented Interfaces:

ModelEvaluation.BiasConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable

Enclosing class:

ModelEvaluation.BiasConfig

public static final class ModelEvaluation.BiasConfig.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>
implements ModelEvaluation.BiasConfigOrBuilder

 Configuration for bias detection.
 

Protobuf type google.cloud.aiplatform.v1beta1.ModelEvaluation.BiasConfig

Method Summary

Modifier and Type	Method and Description
ModelEvaluation.BiasConfig.Builder	addAllLabels(Iterable<String> values) Positive labels selection on the target field.
ModelEvaluation.BiasConfig.Builder	addLabels(String value) Positive labels selection on the target field.
ModelEvaluation.BiasConfig.Builder	addLabelsBytes(com.google.protobuf.ByteString value) Positive labels selection on the target field.
ModelEvaluation.BiasConfig.Builder	addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
ModelEvaluation.BiasConfig	build()
ModelEvaluation.BiasConfig	buildPartial()
ModelEvaluation.BiasConfig.Builder	clear()
ModelEvaluation.BiasConfig.Builder	clearBiasSlices() Specification for how the data should be sliced for bias.
ModelEvaluation.BiasConfig.Builder	clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
ModelEvaluation.BiasConfig.Builder	clearLabels() Positive labels selection on the target field.
ModelEvaluation.BiasConfig.Builder	clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
ModelEvaluation.BiasConfig.Builder	clone()
ModelEvaluationSlice.Slice.SliceSpec	getBiasSlices() Specification for how the data should be sliced for bias.
ModelEvaluationSlice.Slice.SliceSpec.Builder	getBiasSlicesBuilder() Specification for how the data should be sliced for bias.
ModelEvaluationSlice.Slice.SliceSpecOrBuilder	getBiasSlicesOrBuilder() Specification for how the data should be sliced for bias.
ModelEvaluation.BiasConfig	getDefaultInstanceForType()
static com.google.protobuf.Descriptors.Descriptor	getDescriptor()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType()
String	getLabels(int index) Positive labels selection on the target field.
com.google.protobuf.ByteString	getLabelsBytes(int index) Positive labels selection on the target field.
int	getLabelsCount() Positive labels selection on the target field.
com.google.protobuf.ProtocolStringList	getLabelsList() Positive labels selection on the target field.
boolean	hasBiasSlices() Specification for how the data should be sliced for bias.
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable	internalGetFieldAccessorTable()
boolean	isInitialized()
ModelEvaluation.BiasConfig.Builder	mergeBiasSlices(ModelEvaluationSlice.Slice.SliceSpec value) Specification for how the data should be sliced for bias.
ModelEvaluation.BiasConfig.Builder	mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
ModelEvaluation.BiasConfig.Builder	mergeFrom(com.google.protobuf.Message other)
ModelEvaluation.BiasConfig.Builder	mergeFrom(ModelEvaluation.BiasConfig other)
ModelEvaluation.BiasConfig.Builder	mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
ModelEvaluation.BiasConfig.Builder	setBiasSlices(ModelEvaluationSlice.Slice.SliceSpec.Builder builderForValue) Specification for how the data should be sliced for bias.
ModelEvaluation.BiasConfig.Builder	setBiasSlices(ModelEvaluationSlice.Slice.SliceSpec value) Specification for how the data should be sliced for bias.
ModelEvaluation.BiasConfig.Builder	setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
ModelEvaluation.BiasConfig.Builder	setLabels(int index, String value) Positive labels selection on the target field.
ModelEvaluation.BiasConfig.Builder	setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
ModelEvaluation.BiasConfig.Builder	setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)

Methods inherited from class com.google.protobuf.GeneratedMessageV3.Builder

getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3

Methods inherited from class com.google.protobuf.AbstractMessage.Builder

findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder

addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.Message.Builder

mergeDelimitedFrom, mergeDelimitedFrom

Method Detail

getDescriptor

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

internalGetFieldAccessorTable

protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Specified by:

internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

clear

public ModelEvaluation.BiasConfig.Builder clear()

Specified by:

clear in interface com.google.protobuf.Message.Builder

Specified by:

clear in interface com.google.protobuf.MessageLite.Builder

Overrides:

clear in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

getDescriptorForType

public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()

Specified by:

getDescriptorForType in interface com.google.protobuf.Message.Builder

Specified by:

getDescriptorForType in interface com.google.protobuf.MessageOrBuilder

Overrides:

getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

getDefaultInstanceForType

public ModelEvaluation.BiasConfig getDefaultInstanceForType()

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

build

public ModelEvaluation.BiasConfig build()

Specified by:

build in interface com.google.protobuf.Message.Builder

Specified by:

build in interface com.google.protobuf.MessageLite.Builder

buildPartial

public ModelEvaluation.BiasConfig buildPartial()

Specified by:

buildPartial in interface com.google.protobuf.Message.Builder

Specified by:

buildPartial in interface com.google.protobuf.MessageLite.Builder

clone

public ModelEvaluation.BiasConfig.Builder clone()

Specified by:

clone in interface com.google.protobuf.Message.Builder

Specified by:

clone in interface com.google.protobuf.MessageLite.Builder

Overrides:

clone in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

setField

public ModelEvaluation.BiasConfig.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                   Object value)

Specified by:

setField in interface com.google.protobuf.Message.Builder

Overrides:

setField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

clearField

public ModelEvaluation.BiasConfig.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)

Specified by:

clearField in interface com.google.protobuf.Message.Builder

Overrides:

clearField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

clearOneof

public ModelEvaluation.BiasConfig.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)

Specified by:

clearOneof in interface com.google.protobuf.Message.Builder

Overrides:

clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

setRepeatedField

public ModelEvaluation.BiasConfig.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                           int index,
                                                           Object value)

Specified by:

setRepeatedField in interface com.google.protobuf.Message.Builder

Overrides:

setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

addRepeatedField

public ModelEvaluation.BiasConfig.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                           Object value)

Specified by:

addRepeatedField in interface com.google.protobuf.Message.Builder

Overrides:

addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

mergeFrom

public ModelEvaluation.BiasConfig.Builder mergeFrom(com.google.protobuf.Message other)

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelEvaluation.BiasConfig.Builder>

mergeFrom

public ModelEvaluation.BiasConfig.Builder mergeFrom(ModelEvaluation.BiasConfig other)

isInitialized

public final boolean isInitialized()

Specified by:

isInitialized in interface com.google.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

mergeFrom

public ModelEvaluation.BiasConfig.Builder mergeFrom(com.google.protobuf.CodedInputStream input,
                                                    com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                             throws IOException

Specified by:

mergeFrom in interface com.google.protobuf.Message.Builder

Specified by:

mergeFrom in interface com.google.protobuf.MessageLite.Builder

Overrides:

mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ModelEvaluation.BiasConfig.Builder>

Throws:

IOException

hasBiasSlices

public boolean hasBiasSlices()

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

Specified by:

hasBiasSlices in interface ModelEvaluation.BiasConfigOrBuilder

Returns:

Whether the biasSlices field is set.

getBiasSlices

public ModelEvaluationSlice.Slice.SliceSpec getBiasSlices()

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

Specified by:

getBiasSlices in interface ModelEvaluation.BiasConfigOrBuilder

Returns:

The biasSlices.

setBiasSlices

public ModelEvaluation.BiasConfig.Builder setBiasSlices(ModelEvaluationSlice.Slice.SliceSpec value)

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

setBiasSlices

public ModelEvaluation.BiasConfig.Builder setBiasSlices(ModelEvaluationSlice.Slice.SliceSpec.Builder builderForValue)

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

mergeBiasSlices

public ModelEvaluation.BiasConfig.Builder mergeBiasSlices(ModelEvaluationSlice.Slice.SliceSpec value)

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

clearBiasSlices

public ModelEvaluation.BiasConfig.Builder clearBiasSlices()

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

getBiasSlicesBuilder

public ModelEvaluationSlice.Slice.SliceSpec.Builder getBiasSlicesBuilder()

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

getBiasSlicesOrBuilder

public ModelEvaluationSlice.Slice.SliceSpecOrBuilder getBiasSlicesOrBuilder()

 Specification for how the data should be sliced for bias. It contains a
 list of slices, with limitation of two slices. The first slice of data
 will be the slice_a. The second slice in the list (slice_b) will be
 compared against the first slice. If only a single slice is provided,
 then slice_a will be compared against "not slice_a".
 Below are examples with feature "education" with value "low", "medium",
 "high" in the dataset:

 Example 1:

     bias_slices = [{'education': 'low'}]

 A single slice provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'medium' or 'high'.

 Example 2:

     bias_slices = [{'education': 'low'},
                    {'education': 'high'}]

 Two slices provided. In this case, slice_a is the collection of data
 with 'education' equals 'low', and slice_b is the collection of data with
 'education' equals 'high'.
 

.google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.SliceSpec bias_slices = 1;

Specified by:

getBiasSlicesOrBuilder in interface ModelEvaluation.BiasConfigOrBuilder

getLabelsList

public com.google.protobuf.ProtocolStringList getLabelsList()

 Positive labels selection on the target field.
 

repeated string labels = 2;

Specified by:

getLabelsList in interface ModelEvaluation.BiasConfigOrBuilder

Returns:

A list containing the labels.

getLabelsCount

public int getLabelsCount()

 Positive labels selection on the target field.
 

repeated string labels = 2;

Specified by:

getLabelsCount in interface ModelEvaluation.BiasConfigOrBuilder

Returns:

The count of labels.

getLabels

public String getLabels(int index)

 Positive labels selection on the target field.
 

repeated string labels = 2;

Specified by:

getLabels in interface ModelEvaluation.BiasConfigOrBuilder

Parameters:

index - The index of the element to return.

Returns:

The labels at the given index.

getLabelsBytes

public com.google.protobuf.ByteString getLabelsBytes(int index)

 Positive labels selection on the target field.
 

repeated string labels = 2;

Specified by:

getLabelsBytes in interface ModelEvaluation.BiasConfigOrBuilder

Parameters:

index - The index of the value to return.

Returns:

The bytes of the labels at the given index.

setLabels

public ModelEvaluation.BiasConfig.Builder setLabels(int index,
                                                    String value)

 Positive labels selection on the target field.
 

repeated string labels = 2;

Parameters:

index - The index to set the value at.

value - The labels to set.

Returns:

This builder for chaining.

addLabels

public ModelEvaluation.BiasConfig.Builder addLabels(String value)

 Positive labels selection on the target field.
 

repeated string labels = 2;

Parameters:

value - The labels to add.

Returns:

This builder for chaining.

addAllLabels

public ModelEvaluation.BiasConfig.Builder addAllLabels(Iterable<String> values)

 Positive labels selection on the target field.
 

repeated string labels = 2;

Parameters:

values - The labels to add.

Returns:

This builder for chaining.

clearLabels

public ModelEvaluation.BiasConfig.Builder clearLabels()

 Positive labels selection on the target field.
 

repeated string labels = 2;

Returns:

This builder for chaining.

addLabelsBytes

public ModelEvaluation.BiasConfig.Builder addLabelsBytes(com.google.protobuf.ByteString value)

 Positive labels selection on the target field.
 

repeated string labels = 2;

Parameters:

value - The bytes of the labels to add.

Returns:

This builder for chaining.

setUnknownFields

public final ModelEvaluation.BiasConfig.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)

Specified by:

setUnknownFields in interface com.google.protobuf.Message.Builder

Overrides:

setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>

mergeUnknownFields

public final ModelEvaluation.BiasConfig.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)

Specified by:

mergeUnknownFields in interface com.google.protobuf.Message.Builder

Overrides:

mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ModelEvaluation.BiasConfig.Builder>