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public static final class ExplanationMetadata.InputMetadata extends GeneratedMessageV3 implements ExplanationMetadata.InputMetadataOrBuilderMetadata of the input of a feature.
Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata
Inheritance
Object > AbstractMessageLite<MessageType,BuilderType> > AbstractMessage > GeneratedMessageV3 > ExplanationMetadata.InputMetadataImplements
ExplanationMetadata.InputMetadataOrBuilderStatic Fields
DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER
public static final int DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
ENCODED_BASELINES_FIELD_NUMBER
public static final int ENCODED_BASELINES_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
ENCODED_TENSOR_NAME_FIELD_NUMBER
public static final int ENCODED_TENSOR_NAME_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
ENCODING_FIELD_NUMBER
public static final int ENCODING_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
FEATURE_VALUE_DOMAIN_FIELD_NUMBER
public static final int FEATURE_VALUE_DOMAIN_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
GROUP_NAME_FIELD_NUMBER
public static final int GROUP_NAME_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
INDEX_FEATURE_MAPPING_FIELD_NUMBER
public static final int INDEX_FEATURE_MAPPING_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
INDICES_TENSOR_NAME_FIELD_NUMBER
public static final int INDICES_TENSOR_NAME_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
INPUT_BASELINES_FIELD_NUMBER
public static final int INPUT_BASELINES_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
INPUT_TENSOR_NAME_FIELD_NUMBER
public static final int INPUT_TENSOR_NAME_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
MODALITY_FIELD_NUMBER
public static final int MODALITY_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
VISUALIZATION_FIELD_NUMBER
public static final int VISUALIZATION_FIELD_NUMBER| Field Value | |
|---|---|
| Type | Description |
int |
|
Static Methods
getDefaultInstance()
public static ExplanationMetadata.InputMetadata getDefaultInstance()| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
newBuilder()
public static ExplanationMetadata.InputMetadata.Builder newBuilder()| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Builder |
|
newBuilder(ExplanationMetadata.InputMetadata prototype)
public static ExplanationMetadata.InputMetadata.Builder newBuilder(ExplanationMetadata.InputMetadata prototype)| Parameter | |
|---|---|
| Name | Description |
prototype |
ExplanationMetadata.InputMetadata |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Builder |
|
parseDelimitedFrom(InputStream input)
public static ExplanationMetadata.InputMetadata parseDelimitedFrom(InputStream input)| Parameter | |
|---|---|
| Name | Description |
input |
InputStream |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata.InputMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
InputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
parseFrom(byte[] data)
public static ExplanationMetadata.InputMetadata parseFrom(byte[] data)| Parameter | |
|---|---|
| Name | Description |
data |
byte[] |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
InvalidProtocolBufferException |
|
parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata.InputMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
data |
byte[] |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
InvalidProtocolBufferException |
|
parseFrom(ByteString data)
public static ExplanationMetadata.InputMetadata parseFrom(ByteString data)| Parameter | |
|---|---|
| Name | Description |
data |
ByteString |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
InvalidProtocolBufferException |
|
parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata.InputMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
data |
ByteString |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
InvalidProtocolBufferException |
|
parseFrom(CodedInputStream input)
public static ExplanationMetadata.InputMetadata parseFrom(CodedInputStream input)| Parameter | |
|---|---|
| Name | Description |
input |
CodedInputStream |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata.InputMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
parseFrom(InputStream input)
public static ExplanationMetadata.InputMetadata parseFrom(InputStream input)| Parameter | |
|---|---|
| Name | Description |
input |
InputStream |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata.InputMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
InputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
parseFrom(ByteBuffer data)
public static ExplanationMetadata.InputMetadata parseFrom(ByteBuffer data)| Parameter | |
|---|---|
| Name | Description |
data |
ByteBuffer |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
InvalidProtocolBufferException |
|
parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata.InputMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
data |
ByteBuffer |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
| Exceptions | |
|---|---|
| Type | Description |
InvalidProtocolBufferException |
|
parser()
public static Parser<ExplanationMetadata.InputMetadata> parser()| Returns | |
|---|---|
| Type | Description |
Parser<InputMetadata> |
|
Methods
equals(Object obj)
public boolean equals(Object obj)| Parameter | |
|---|---|
| Name | Description |
obj |
Object |
| Returns | |
|---|---|
| Type | Description |
boolean |
|
getDefaultInstanceForType()
public ExplanationMetadata.InputMetadata getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata |
|
getDenseShapeTensorName()
public String getDenseShapeTensorName()Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
string dense_shape_tensor_name = 7;
| Returns | |
|---|---|
| Type | Description |
String |
The denseShapeTensorName. |
getDenseShapeTensorNameBytes()
public ByteString getDenseShapeTensorNameBytes()Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
string dense_shape_tensor_name = 7;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for denseShapeTensorName. |
getEncodedBaselines(int index)
public Value getEncodedBaselines(int index)A list of baselines for the encoded tensor.
The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.
repeated .google.protobuf.Value encoded_baselines = 10;
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
Value |
|
getEncodedBaselinesCount()
public int getEncodedBaselinesCount()A list of baselines for the encoded tensor.
The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.
repeated .google.protobuf.Value encoded_baselines = 10;
| Returns | |
|---|---|
| Type | Description |
int |
|
getEncodedBaselinesList()
public List<Value> getEncodedBaselinesList()A list of baselines for the encoded tensor.
The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.
repeated .google.protobuf.Value encoded_baselines = 10;
| Returns | |
|---|---|
| Type | Description |
List<Value> |
|
getEncodedBaselinesOrBuilder(int index)
public ValueOrBuilder getEncodedBaselinesOrBuilder(int index)A list of baselines for the encoded tensor.
The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.
repeated .google.protobuf.Value encoded_baselines = 10;
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
ValueOrBuilder |
|
getEncodedBaselinesOrBuilderList()
public List<? extends ValueOrBuilder> getEncodedBaselinesOrBuilderList()A list of baselines for the encoded tensor.
The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.
repeated .google.protobuf.Value encoded_baselines = 10;
| Returns | |
|---|---|
| Type | Description |
List<? extends com.google.protobuf.ValueOrBuilder> |
|
getEncodedTensorName()
public String getEncodedTensorName()Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable.
An encoded tensor is generated if the input tensor is encoded by a lookup table.
string encoded_tensor_name = 9;
| Returns | |
|---|---|
| Type | Description |
String |
The encodedTensorName. |
getEncodedTensorNameBytes()
public ByteString getEncodedTensorNameBytes()Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable.
An encoded tensor is generated if the input tensor is encoded by a lookup table.
string encoded_tensor_name = 9;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for encodedTensorName. |
getEncoding()
public ExplanationMetadata.InputMetadata.Encoding getEncoding()Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Encoding |
The encoding. |
getEncodingValue()
public int getEncodingValue()Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
| Returns | |
|---|---|
| Type | Description |
int |
The enum numeric value on the wire for encoding. |
getFeatureValueDomain()
public ExplanationMetadata.InputMetadata.FeatureValueDomain getFeatureValueDomain()The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.FeatureValueDomain |
The featureValueDomain. |
getFeatureValueDomainOrBuilder()
public ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder getFeatureValueDomainOrBuilder()The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder |
|
getGroupName()
public String getGroupName()Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name.
string group_name = 12;
| Returns | |
|---|---|
| Type | Description |
String |
The groupName. |
getGroupNameBytes()
public ByteString getGroupNameBytes()Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name.
string group_name = 12;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for groupName. |
getIndexFeatureMapping(int index)
public String getIndexFeatureMapping(int index)A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
repeated string index_feature_mapping = 8;
| Parameter | |
|---|---|
| Name | Description |
index |
intThe index of the element to return. |
| Returns | |
|---|---|
| Type | Description |
String |
The indexFeatureMapping at the given index. |
getIndexFeatureMappingBytes(int index)
public ByteString getIndexFeatureMappingBytes(int index)A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
repeated string index_feature_mapping = 8;
| Parameter | |
|---|---|
| Name | Description |
index |
intThe index of the value to return. |
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes of the indexFeatureMapping at the given index. |
getIndexFeatureMappingCount()
public int getIndexFeatureMappingCount()A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
repeated string index_feature_mapping = 8;
| Returns | |
|---|---|
| Type | Description |
int |
The count of indexFeatureMapping. |
getIndexFeatureMappingList()
public ProtocolStringList getIndexFeatureMappingList()A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
repeated string index_feature_mapping = 8;
| Returns | |
|---|---|
| Type | Description |
ProtocolStringList |
A list containing the indexFeatureMapping. |
getIndicesTensorName()
public String getIndicesTensorName()Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
string indices_tensor_name = 6;
| Returns | |
|---|---|
| Type | Description |
String |
The indicesTensorName. |
getIndicesTensorNameBytes()
public ByteString getIndicesTensorNameBytes()Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
string indices_tensor_name = 6;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for indicesTensorName. |
getInputBaselines(int index)
public Value getInputBaselines(int index)Baseline inputs for this feature.
If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.
For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.
For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
repeated .google.protobuf.Value input_baselines = 1;
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
Value |
|
getInputBaselinesCount()
public int getInputBaselinesCount()Baseline inputs for this feature.
If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.
For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.
For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
repeated .google.protobuf.Value input_baselines = 1;
| Returns | |
|---|---|
| Type | Description |
int |
|
getInputBaselinesList()
public List<Value> getInputBaselinesList()Baseline inputs for this feature.
If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.
For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.
For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
repeated .google.protobuf.Value input_baselines = 1;
| Returns | |
|---|---|
| Type | Description |
List<Value> |
|
getInputBaselinesOrBuilder(int index)
public ValueOrBuilder getInputBaselinesOrBuilder(int index)Baseline inputs for this feature.
If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.
For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.
For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
repeated .google.protobuf.Value input_baselines = 1;
| Parameter | |
|---|---|
| Name | Description |
index |
int |
| Returns | |
|---|---|
| Type | Description |
ValueOrBuilder |
|
getInputBaselinesOrBuilderList()
public List<? extends ValueOrBuilder> getInputBaselinesOrBuilderList()Baseline inputs for this feature.
If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.
For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.
For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
repeated .google.protobuf.Value input_baselines = 1;
| Returns | |
|---|---|
| Type | Description |
List<? extends com.google.protobuf.ValueOrBuilder> |
|
getInputTensorName()
public String getInputTensorName()Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.
string input_tensor_name = 2;
| Returns | |
|---|---|
| Type | Description |
String |
The inputTensorName. |
getInputTensorNameBytes()
public ByteString getInputTensorNameBytes()Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.
string input_tensor_name = 2;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for inputTensorName. |
getModality()
public String getModality()Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
string modality = 4;
| Returns | |
|---|---|
| Type | Description |
String |
The modality. |
getModalityBytes()
public ByteString getModalityBytes()Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
string modality = 4;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for modality. |
getParserForType()
public Parser<ExplanationMetadata.InputMetadata> getParserForType()| Returns | |
|---|---|
| Type | Description |
Parser<InputMetadata> |
|
getSerializedSize()
public int getSerializedSize()| Returns | |
|---|---|
| Type | Description |
int |
|
getVisualization()
public ExplanationMetadata.InputMetadata.Visualization getVisualization()Visualization configurations for image explanation.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Visualization |
The visualization. |
getVisualizationOrBuilder()
public ExplanationMetadata.InputMetadata.VisualizationOrBuilder getVisualizationOrBuilder()Visualization configurations for image explanation.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.VisualizationOrBuilder |
|
hasFeatureValueDomain()
public boolean hasFeatureValueDomain()The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the featureValueDomain field is set. |
hasVisualization()
public boolean hasVisualization()Visualization configurations for image explanation.
.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the visualization field is set. |
hashCode()
public int hashCode()| Returns | |
|---|---|
| Type | Description |
int |
|
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
newBuilderForType()
public ExplanationMetadata.InputMetadata.Builder newBuilderForType()| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Builder |
|
newBuilderForType(GeneratedMessageV3.BuilderParent parent)
protected ExplanationMetadata.InputMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)| Parameter | |
|---|---|
| Name | Description |
parent |
BuilderParent |
| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Builder |
|
newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)| Parameter | |
|---|---|
| Name | Description |
unused |
UnusedPrivateParameter |
| Returns | |
|---|---|
| Type | Description |
Object |
|
toBuilder()
public ExplanationMetadata.InputMetadata.Builder toBuilder()| Returns | |
|---|---|
| Type | Description |
ExplanationMetadata.InputMetadata.Builder |
|
writeTo(CodedOutputStream output)
public void writeTo(CodedOutputStream output)| Parameter | |
|---|---|
| Name | Description |
output |
CodedOutputStream |
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|