Class ExplanationParameters (3.48.0)

public final class ExplanationParameters extends GeneratedMessageV3 implements ExplanationParametersOrBuilder

Parameters to configure explaining for Model's predictions.

Protobuf type google.cloud.aiplatform.v1.ExplanationParameters

Static Fields

EXAMPLES_FIELD_NUMBER

public static final int EXAMPLES_FIELD_NUMBER
Field Value
Type Description
int

INTEGRATED_GRADIENTS_ATTRIBUTION_FIELD_NUMBER

public static final int INTEGRATED_GRADIENTS_ATTRIBUTION_FIELD_NUMBER
Field Value
Type Description
int

OUTPUT_INDICES_FIELD_NUMBER

public static final int OUTPUT_INDICES_FIELD_NUMBER
Field Value
Type Description
int

SAMPLED_SHAPLEY_ATTRIBUTION_FIELD_NUMBER

public static final int SAMPLED_SHAPLEY_ATTRIBUTION_FIELD_NUMBER
Field Value
Type Description
int

TOP_K_FIELD_NUMBER

public static final int TOP_K_FIELD_NUMBER
Field Value
Type Description
int

XRAI_ATTRIBUTION_FIELD_NUMBER

public static final int XRAI_ATTRIBUTION_FIELD_NUMBER
Field Value
Type Description
int

Static Methods

getDefaultInstance()

public static ExplanationParameters getDefaultInstance()
Returns
Type Description
ExplanationParameters

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

newBuilder()

public static ExplanationParameters.Builder newBuilder()
Returns
Type Description
ExplanationParameters.Builder

newBuilder(ExplanationParameters prototype)

public static ExplanationParameters.Builder newBuilder(ExplanationParameters prototype)
Parameter
Name Description
prototype ExplanationParameters
Returns
Type Description
ExplanationParameters.Builder

parseDelimitedFrom(InputStream input)

public static ExplanationParameters parseDelimitedFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ExplanationParameters parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
IOException

parseFrom(byte[] data)

public static ExplanationParameters parseFrom(byte[] data)
Parameter
Name Description
data byte[]
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static ExplanationParameters parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data byte[]
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static ExplanationParameters parseFrom(ByteString data)
Parameter
Name Description
data ByteString
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static ExplanationParameters parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteString
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static ExplanationParameters parseFrom(CodedInputStream input)
Parameter
Name Description
input CodedInputStream
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static ExplanationParameters parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
IOException

parseFrom(InputStream input)

public static ExplanationParameters parseFrom(InputStream input)
Parameter
Name Description
input InputStream
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ExplanationParameters parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input InputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
IOException

parseFrom(ByteBuffer data)

public static ExplanationParameters parseFrom(ByteBuffer data)
Parameter
Name Description
data ByteBuffer
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static ExplanationParameters parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
data ByteBuffer
extensionRegistry ExtensionRegistryLite
Returns
Type Description
ExplanationParameters
Exceptions
Type Description
InvalidProtocolBufferException

parser()

public static Parser<ExplanationParameters> parser()
Returns
Type Description
Parser<ExplanationParameters>

Methods

equals(Object obj)

public boolean equals(Object obj)
Parameter
Name Description
obj Object
Returns
Type Description
boolean
Overrides

getDefaultInstanceForType()

public ExplanationParameters getDefaultInstanceForType()
Returns
Type Description
ExplanationParameters

getExamples()

public Examples getExamples()

Example-based explanations that returns the nearest neighbors from the provided dataset.

.google.cloud.aiplatform.v1.Examples examples = 7;

Returns
Type Description
Examples

The examples.

getExamplesOrBuilder()

public ExamplesOrBuilder getExamplesOrBuilder()

Example-based explanations that returns the nearest neighbors from the provided dataset.

.google.cloud.aiplatform.v1.Examples examples = 7;

Returns
Type Description
ExamplesOrBuilder

getIntegratedGradientsAttribution()

public IntegratedGradientsAttribution getIntegratedGradientsAttribution()

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

.google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;

Returns
Type Description
IntegratedGradientsAttribution

The integratedGradientsAttribution.

getIntegratedGradientsAttributionOrBuilder()

public IntegratedGradientsAttributionOrBuilder getIntegratedGradientsAttributionOrBuilder()

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

.google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;

Returns
Type Description
IntegratedGradientsAttributionOrBuilder

getMethodCase()

public ExplanationParameters.MethodCase getMethodCase()
Returns
Type Description
ExplanationParameters.MethodCase

getOutputIndices()

public ListValue getOutputIndices()

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining.

If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs.

Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

.google.protobuf.ListValue output_indices = 5;

Returns
Type Description
ListValue

The outputIndices.

getOutputIndicesOrBuilder()

public ListValueOrBuilder getOutputIndicesOrBuilder()

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining.

If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs.

Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

.google.protobuf.ListValue output_indices = 5;

Returns
Type Description
ListValueOrBuilder

getParserForType()

public Parser<ExplanationParameters> getParserForType()
Returns
Type Description
Parser<ExplanationParameters>
Overrides

getSampledShapleyAttribution()

public SampledShapleyAttribution getSampledShapleyAttribution()

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

.google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;

Returns
Type Description
SampledShapleyAttribution

The sampledShapleyAttribution.

getSampledShapleyAttributionOrBuilder()

public SampledShapleyAttributionOrBuilder getSampledShapleyAttributionOrBuilder()

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

.google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;

Returns
Type Description
SampledShapleyAttributionOrBuilder

getSerializedSize()

public int getSerializedSize()
Returns
Type Description
int
Overrides

getTopK()

public int getTopK()

If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs.

int32 top_k = 4;

Returns
Type Description
int

The topK.

getXraiAttribution()

public XraiAttribution getXraiAttribution()

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825

XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.

.google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;

Returns
Type Description
XraiAttribution

The xraiAttribution.

getXraiAttributionOrBuilder()

public XraiAttributionOrBuilder getXraiAttributionOrBuilder()

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825

XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.

.google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;

Returns
Type Description
XraiAttributionOrBuilder

hasExamples()

public boolean hasExamples()

Example-based explanations that returns the nearest neighbors from the provided dataset.

.google.cloud.aiplatform.v1.Examples examples = 7;

Returns
Type Description
boolean

Whether the examples field is set.

hasIntegratedGradientsAttribution()

public boolean hasIntegratedGradientsAttribution()

An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

.google.cloud.aiplatform.v1.IntegratedGradientsAttribution integrated_gradients_attribution = 2;

Returns
Type Description
boolean

Whether the integratedGradientsAttribution field is set.

hasOutputIndices()

public boolean hasOutputIndices()

If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining.

If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs.

Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes).

.google.protobuf.ListValue output_indices = 5;

Returns
Type Description
boolean

Whether the outputIndices field is set.

hasSampledShapleyAttribution()

public boolean hasSampledShapleyAttribution()

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265.

.google.cloud.aiplatform.v1.SampledShapleyAttribution sampled_shapley_attribution = 1;

Returns
Type Description
boolean

Whether the sampledShapleyAttribution field is set.

hasXraiAttribution()

public boolean hasXraiAttribution()

An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825

XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead.

.google.cloud.aiplatform.v1.XraiAttribution xrai_attribution = 3;

Returns
Type Description
boolean

Whether the xraiAttribution field is set.

hashCode()

public int hashCode()
Returns
Type Description
int
Overrides

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

newBuilderForType()

public ExplanationParameters.Builder newBuilderForType()
Returns
Type Description
ExplanationParameters.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected ExplanationParameters.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Parameter
Name Description
parent BuilderParent
Returns
Type Description
ExplanationParameters.Builder
Overrides

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Parameter
Name Description
unused UnusedPrivateParameter
Returns
Type Description
Object
Overrides

toBuilder()

public ExplanationParameters.Builder toBuilder()
Returns
Type Description
ExplanationParameters.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)
Parameter
Name Description
output CodedOutputStream
Overrides
Exceptions
Type Description
IOException