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public static final class ExplanationMetadata.Builder extends GeneratedMessageV3.Builder<ExplanationMetadata.Builder> implements ExplanationMetadataOrBuilder
Metadata describing the Model's input and output for explanation.
Protobuf type google.cloud.aiplatform.v1beta1.ExplanationMetadata
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ExplanationMetadata.BuilderImplements
ExplanationMetadataOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns | |
---|---|
Type | Description |
Descriptor |
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public ExplanationMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
value | Object |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
build()
public ExplanationMetadata build()
Returns | |
---|---|
Type | Description |
ExplanationMetadata |
buildPartial()
public ExplanationMetadata buildPartial()
Returns | |
---|---|
Type | Description |
ExplanationMetadata |
clear()
public ExplanationMetadata.Builder clear()
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
clearFeatureAttributionsSchemaUri()
public ExplanationMetadata.Builder clearFeatureAttributionsSchemaUri()
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 |
ExplanationMetadata.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public ExplanationMetadata.Builder clearField(Descriptors.FieldDescriptor field)
Parameter | |
---|---|
Name | Description |
field | FieldDescriptor |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
clearInputs()
public ExplanationMetadata.Builder clearInputs()
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
clearLatentSpaceSource()
public ExplanationMetadata.Builder clearLatentSpaceSource()
Name of the source to generate embeddings for example based explanations.
string latent_space_source = 5;
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public ExplanationMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter | |
---|---|
Name | Description |
oneof | OneofDescriptor |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
clearOutputs()
public ExplanationMetadata.Builder clearOutputs()
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
clone()
public ExplanationMetadata.Builder clone()
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
containsInputs(String key)
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 |
Returns | |
---|---|
Type | Description |
boolean |
containsOutputs(String key)
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 |
Returns | |
---|---|
Type | Description |
boolean |
getDefaultInstanceForType()
public ExplanationMetadata getDefaultInstanceForType()
Returns | |
---|---|
Type | Description |
ExplanationMetadata |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns | |
---|---|
Type | Description |
Descriptor |
getFeatureAttributionsSchemaUri()
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. |
getFeatureAttributionsSchemaUriBytes()
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. |
getInputs() (deprecated)
public Map<String,ExplanationMetadata.InputMetadata> getInputs()
Use #getInputsMap() instead.
Returns | |
---|---|
Type | Description |
Map<String,InputMetadata> |
getInputsCount()
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 |
getInputsMap()
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];
Returns | |
---|---|
Type | Description |
Map<String,InputMetadata> |
getInputsOrDefault(String key, ExplanationMetadata.InputMetadata defaultValue)
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];
Parameters | |
---|---|
Name | Description |
key | String |
defaultValue | ExplanationMetadata.InputMetadata |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.InputMetadata |
getInputsOrThrow(String key)
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 |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.InputMetadata |
getLatentSpaceSource()
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. |
getLatentSpaceSourceBytes()
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. |
getMutableInputs() (deprecated)
public Map<String,ExplanationMetadata.InputMetadata> getMutableInputs()
Use alternate mutation accessors instead.
Returns | |
---|---|
Type | Description |
Map<String,InputMetadata> |
getMutableOutputs() (deprecated)
public Map<String,ExplanationMetadata.OutputMetadata> getMutableOutputs()
Use alternate mutation accessors instead.
Returns | |
---|---|
Type | Description |
Map<String,OutputMetadata> |
getOutputs() (deprecated)
public Map<String,ExplanationMetadata.OutputMetadata> getOutputs()
Use #getOutputsMap() instead.
Returns | |
---|---|
Type | Description |
Map<String,OutputMetadata> |
getOutputsCount()
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 |
getOutputsMap()
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];
Returns | |
---|---|
Type | Description |
Map<String,OutputMetadata> |
getOutputsOrDefault(String key, ExplanationMetadata.OutputMetadata defaultValue)
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];
Parameters | |
---|---|
Name | Description |
key | String |
defaultValue | ExplanationMetadata.OutputMetadata |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.OutputMetadata |
getOutputsOrThrow(String key)
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 |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.OutputMetadata |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns | |
---|---|
Type | Description |
FieldAccessorTable |
internalGetMapField(int number)
protected MapField internalGetMapField(int number)
Parameter | |
---|---|
Name | Description |
number | int |
Returns | |
---|---|
Type | Description |
MapField |
internalGetMutableMapField(int number)
protected MapField internalGetMutableMapField(int number)
Parameter | |
---|---|
Name | Description |
number | int |
Returns | |
---|---|
Type | Description |
MapField |
isInitialized()
public final boolean isInitialized()
Returns | |
---|---|
Type | Description |
boolean |
mergeFrom(ExplanationMetadata other)
public ExplanationMetadata.Builder mergeFrom(ExplanationMetadata other)
Parameter | |
---|---|
Name | Description |
other | ExplanationMetadata |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public ExplanationMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters | |
---|---|
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
Exceptions | |
---|---|
Type | Description |
IOException |
mergeFrom(Message other)
public ExplanationMetadata.Builder mergeFrom(Message other)
Parameter | |
---|---|
Name | Description |
other | Message |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final ExplanationMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
putAllInputs(Map<String,ExplanationMetadata.InputMetadata> values)
public ExplanationMetadata.Builder putAllInputs(Map<String,ExplanationMetadata.InputMetadata> values)
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 |
values | Map<String,InputMetadata> |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
putAllOutputs(Map<String,ExplanationMetadata.OutputMetadata> values)
public ExplanationMetadata.Builder putAllOutputs(Map<String,ExplanationMetadata.OutputMetadata> values)
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 |
values | Map<String,OutputMetadata> |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
putInputs(String key, ExplanationMetadata.InputMetadata value)
public ExplanationMetadata.Builder putInputs(String key, ExplanationMetadata.InputMetadata value)
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];
Parameters | |
---|---|
Name | Description |
key | String |
value | ExplanationMetadata.InputMetadata |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
putOutputs(String key, ExplanationMetadata.OutputMetadata value)
public ExplanationMetadata.Builder putOutputs(String key, ExplanationMetadata.OutputMetadata value)
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];
Parameters | |
---|---|
Name | Description |
key | String |
value | ExplanationMetadata.OutputMetadata |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
removeInputs(String key)
public ExplanationMetadata.Builder removeInputs(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 |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
removeOutputs(String key)
public ExplanationMetadata.Builder removeOutputs(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 |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
setFeatureAttributionsSchemaUri(String value)
public ExplanationMetadata.Builder setFeatureAttributionsSchemaUri(String value)
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;
Parameter | |
---|---|
Name | Description |
value | String The featureAttributionsSchemaUri to set. |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder | This builder for chaining. |
setFeatureAttributionsSchemaUriBytes(ByteString value)
public ExplanationMetadata.Builder setFeatureAttributionsSchemaUriBytes(ByteString value)
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;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for featureAttributionsSchemaUri to set. |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder | This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public ExplanationMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
value | Object |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
setLatentSpaceSource(String value)
public ExplanationMetadata.Builder setLatentSpaceSource(String value)
Name of the source to generate embeddings for example based explanations.
string latent_space_source = 5;
Parameter | |
---|---|
Name | Description |
value | String The latentSpaceSource to set. |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder | This builder for chaining. |
setLatentSpaceSourceBytes(ByteString value)
public ExplanationMetadata.Builder setLatentSpaceSourceBytes(ByteString value)
Name of the source to generate embeddings for example based explanations.
string latent_space_source = 5;
Parameter | |
---|---|
Name | Description |
value | ByteString The bytes for latentSpaceSource to set. |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder | This builder for chaining. |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public ExplanationMetadata.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters | |
---|---|
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |
setUnknownFields(UnknownFieldSet unknownFields)
public final ExplanationMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields | UnknownFieldSet |
Returns | |
---|---|
Type | Description |
ExplanationMetadata.Builder |