public final class ExplanationMetadata extends GeneratedMessageV3 implements ExplanationMetadataOrBuilder
Metadata describing the Model's input and output for explanation.
Protobuf type google.cloud.aiplatform.v1beta1.ExplanationMetadata
Inherited Members
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)
com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)
com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
Static Fields
public static final int FEATURE_ATTRIBUTIONS_SCHEMA_URI_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int INPUTS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int LATENT_SPACE_SOURCE_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
public static final int OUTPUTS_FIELD_NUMBER
| Field Value |
|---|
| Type | Description |
int | |
Static Methods
public static ExplanationMetadata getDefaultInstance()
public static final Descriptors.Descriptor getDescriptor()
public static ExplanationMetadata.Builder newBuilder()
public static ExplanationMetadata.Builder newBuilder(ExplanationMetadata prototype)
public static ExplanationMetadata parseDelimitedFrom(InputStream input)
public static ExplanationMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata parseFrom(byte[] data)
| Parameter |
|---|
| Name | Description |
data | byte[]
|
public static ExplanationMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata parseFrom(ByteString data)
public static ExplanationMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata parseFrom(CodedInputStream input)
public static ExplanationMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata parseFrom(InputStream input)
public static ExplanationMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)
public static ExplanationMetadata parseFrom(ByteBuffer data)
public static ExplanationMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)
public static Parser<ExplanationMetadata> parser()
Methods
public boolean containsInputs(String key)
Required. Map from feature names to feature input metadata. Keys are the
name of the features. Values are the specification of the feature.
An empty InputMetadata is valid. It describes a text feature which has the
name specified as the key in
ExplanationMetadata.inputs.
The baseline of the empty feature is chosen by Vertex AI.
For Vertex AI-provided Tensorflow images, the key can be any friendly
name of the feature. Once specified,
featureAttributions
are keyed by this key (if not grouped with another feature).
For custom images, the key must match with the key in
instance.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
| Parameter |
|---|
| Name | Description |
key | String
|
public boolean containsOutputs(String key)
Required. Map from output names to output metadata.
For Vertex AI-provided Tensorflow images, keys can be any user defined
string that consists of any UTF-8 characters.
For custom images, keys are the name of the output field in the prediction
to be explained.
Currently only one key is allowed.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
| Parameter |
|---|
| Name | Description |
key | String
|
public boolean equals(Object obj)
| Parameter |
|---|
| Name | Description |
obj | Object
|
Overrides
public ExplanationMetadata getDefaultInstanceForType()
public String getFeatureAttributionsSchemaUri()
Points to a YAML file stored on Google Cloud Storage describing the format
of the feature
attributions.
The schema is defined as an OpenAPI 3.0.2 Schema
Object.
AutoML tabular Models always have this field populated by Vertex AI.
Note: The URI given on output may be different, including the URI scheme,
than the one given on input. The output URI will point to a location where
the user only has a read access.
string feature_attributions_schema_uri = 3;
| Returns |
|---|
| Type | Description |
String | The featureAttributionsSchemaUri.
|
public ByteString getFeatureAttributionsSchemaUriBytes()
Points to a YAML file stored on Google Cloud Storage describing the format
of the feature
attributions.
The schema is defined as an OpenAPI 3.0.2 Schema
Object.
AutoML tabular Models always have this field populated by Vertex AI.
Note: The URI given on output may be different, including the URI scheme,
than the one given on input. The output URI will point to a location where
the user only has a read access.
string feature_attributions_schema_uri = 3;
| Returns |
|---|
| Type | Description |
ByteString | The bytes for featureAttributionsSchemaUri.
|
public Map<String,ExplanationMetadata.InputMetadata> getInputs()
public int getInputsCount()
Required. Map from feature names to feature input metadata. Keys are the
name of the features. Values are the specification of the feature.
An empty InputMetadata is valid. It describes a text feature which has the
name specified as the key in
ExplanationMetadata.inputs.
The baseline of the empty feature is chosen by Vertex AI.
For Vertex AI-provided Tensorflow images, the key can be any friendly
name of the feature. Once specified,
featureAttributions
are keyed by this key (if not grouped with another feature).
For custom images, the key must match with the key in
instance.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
| Returns |
|---|
| Type | Description |
int | |
public Map<String,ExplanationMetadata.InputMetadata> getInputsMap()
Required. Map from feature names to feature input metadata. Keys are the
name of the features. Values are the specification of the feature.
An empty InputMetadata is valid. It describes a text feature which has the
name specified as the key in
ExplanationMetadata.inputs.
The baseline of the empty feature is chosen by Vertex AI.
For Vertex AI-provided Tensorflow images, the key can be any friendly
name of the feature. Once specified,
featureAttributions
are keyed by this key (if not grouped with another feature).
For custom images, the key must match with the key in
instance.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
public ExplanationMetadata.InputMetadata getInputsOrDefault(String key, ExplanationMetadata.InputMetadata defaultValue)
Required. Map from feature names to feature input metadata. Keys are the
name of the features. Values are the specification of the feature.
An empty InputMetadata is valid. It describes a text feature which has the
name specified as the key in
ExplanationMetadata.inputs.
The baseline of the empty feature is chosen by Vertex AI.
For Vertex AI-provided Tensorflow images, the key can be any friendly
name of the feature. Once specified,
featureAttributions
are keyed by this key (if not grouped with another feature).
For custom images, the key must match with the key in
instance.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
public ExplanationMetadata.InputMetadata getInputsOrThrow(String key)
Required. Map from feature names to feature input metadata. Keys are the
name of the features. Values are the specification of the feature.
An empty InputMetadata is valid. It describes a text feature which has the
name specified as the key in
ExplanationMetadata.inputs.
The baseline of the empty feature is chosen by Vertex AI.
For Vertex AI-provided Tensorflow images, the key can be any friendly
name of the feature. Once specified,
featureAttributions
are keyed by this key (if not grouped with another feature).
For custom images, the key must match with the key in
instance.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
| Parameter |
|---|
| Name | Description |
key | String
|
public String getLatentSpaceSource()
Name of the source to generate embeddings for example based explanations.
string latent_space_source = 5;
| Returns |
|---|
| Type | Description |
String | The latentSpaceSource.
|
public ByteString getLatentSpaceSourceBytes()
Name of the source to generate embeddings for example based explanations.
string latent_space_source = 5;
| Returns |
|---|
| Type | Description |
ByteString | The bytes for latentSpaceSource.
|
public Map<String,ExplanationMetadata.OutputMetadata> getOutputs()
public int getOutputsCount()
Required. Map from output names to output metadata.
For Vertex AI-provided Tensorflow images, keys can be any user defined
string that consists of any UTF-8 characters.
For custom images, keys are the name of the output field in the prediction
to be explained.
Currently only one key is allowed.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
| Returns |
|---|
| Type | Description |
int | |
public Map<String,ExplanationMetadata.OutputMetadata> getOutputsMap()
Required. Map from output names to output metadata.
For Vertex AI-provided Tensorflow images, keys can be any user defined
string that consists of any UTF-8 characters.
For custom images, keys are the name of the output field in the prediction
to be explained.
Currently only one key is allowed.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
public ExplanationMetadata.OutputMetadata getOutputsOrDefault(String key, ExplanationMetadata.OutputMetadata defaultValue)
Required. Map from output names to output metadata.
For Vertex AI-provided Tensorflow images, keys can be any user defined
string that consists of any UTF-8 characters.
For custom images, keys are the name of the output field in the prediction
to be explained.
Currently only one key is allowed.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
public ExplanationMetadata.OutputMetadata getOutputsOrThrow(String key)
Required. Map from output names to output metadata.
For Vertex AI-provided Tensorflow images, keys can be any user defined
string that consists of any UTF-8 characters.
For custom images, keys are the name of the output field in the prediction
to be explained.
Currently only one key is allowed.
map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
| Parameter |
|---|
| Name | Description |
key | String
|
public Parser<ExplanationMetadata> getParserForType()
Overrides
public int getSerializedSize()
| Returns |
|---|
| Type | Description |
int | |
Overrides
| Returns |
|---|
| Type | Description |
int | |
Overrides
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Overrides
protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
| Parameter |
|---|
| Name | Description |
number | int
|
| Returns |
|---|
| Type | Description |
com.google.protobuf.MapFieldReflectionAccessor | |
Overrides
com.google.protobuf.GeneratedMessageV3.internalGetMapFieldReflection(int)
public final boolean isInitialized()
Overrides
public ExplanationMetadata.Builder newBuilderForType()
protected ExplanationMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)
Overrides
protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)
Overrides
public ExplanationMetadata.Builder toBuilder()
public void writeTo(CodedOutputStream output)
Overrides
