com.google.cloud.aiplatform.v1beta1

Interface ExplanationMetadataOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

ExplanationMetadata, ExplanationMetadata.Builder

public interface ExplanationMetadataOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
boolean	containsInputs(String key) Required.
boolean	containsOutputs(String key) Required.
String	getFeatureAttributionsSchemaUri() Points to a YAML file stored on Google Cloud Storage describing the format of the [feature attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions].
com.google.protobuf.ByteString	getFeatureAttributionsSchemaUriBytes() Points to a YAML file stored on Google Cloud Storage describing the format of the [feature attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions].
Map<String,ExplanationMetadata.InputMetadata>	getInputs() Deprecated.
int	getInputsCount() Required.
Map<String,ExplanationMetadata.InputMetadata>	getInputsMap() Required.
ExplanationMetadata.InputMetadata	getInputsOrDefault(String key, ExplanationMetadata.InputMetadata defaultValue) Required.
ExplanationMetadata.InputMetadata	getInputsOrThrow(String key) Required.
String	getLatentSpaceSource() Name of the source to generate embeddings for example based explanations.
com.google.protobuf.ByteString	getLatentSpaceSourceBytes() Name of the source to generate embeddings for example based explanations.
Map<String,ExplanationMetadata.OutputMetadata>	getOutputs() Deprecated.
int	getOutputsCount() Required.
Map<String,ExplanationMetadata.OutputMetadata>	getOutputsMap() Required.
ExplanationMetadata.OutputMetadata	getOutputsOrDefault(String key, ExplanationMetadata.OutputMetadata defaultValue) Required.
ExplanationMetadata.OutputMetadata	getOutputsOrThrow(String key) Required.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

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

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getInputsCount

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][google.cloud.aiplatform.v1beta1.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][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] are keyed by
 this key (if not grouped with another feature).
 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances].
 

map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

containsInputs

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][google.cloud.aiplatform.v1beta1.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][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] are keyed by
 this key (if not grouped with another feature).
 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances].
 

map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

getInputs

@Deprecated
Map<String,ExplanationMetadata.InputMetadata> getInputs()

Deprecated.

Use getInputsMap() instead.

getInputsMap

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][google.cloud.aiplatform.v1beta1.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][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] are keyed by
 this key (if not grouped with another feature).
 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances].
 

map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

getInputsOrDefault

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][google.cloud.aiplatform.v1beta1.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][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] are keyed by
 this key (if not grouped with another feature).
 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances].
 

map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

getInputsOrThrow

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][google.cloud.aiplatform.v1beta1.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][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions] are keyed by
 this key (if not grouped with another feature).
 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances].
 

map<string, .google.cloud.aiplatform.v1beta1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

getOutputsCount

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];

containsOutputs

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];

getOutputs

@Deprecated
Map<String,ExplanationMetadata.OutputMetadata> getOutputs()

Deprecated.

Use getOutputsMap() instead.

getOutputsMap

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];

getOutputsOrDefault

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];

getOutputsOrThrow

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];

getFeatureAttributionsSchemaUri

String getFeatureAttributionsSchemaUri()

 Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 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:

The featureAttributionsSchemaUri.

getFeatureAttributionsSchemaUriBytes

com.google.protobuf.ByteString getFeatureAttributionsSchemaUriBytes()

 Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature attributions][google.cloud.aiplatform.v1beta1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 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:

The bytes for featureAttributionsSchemaUri.

getLatentSpaceSource

String getLatentSpaceSource()

 Name of the source to generate embeddings for example based explanations.
 

string latent_space_source = 5;

Returns:

The latentSpaceSource.

getLatentSpaceSourceBytes

com.google.protobuf.ByteString getLatentSpaceSourceBytes()

 Name of the source to generate embeddings for example based explanations.
 

string latent_space_source = 5;

Returns:

The bytes for latentSpaceSource.