Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ExplanationMetadata.
Metadata describing the Model's input and output for explanation.
Generated from protobuf message google.cloud.aiplatform.v1.ExplanationMetadata
Methods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ inputs |
array|Google\Protobuf\Internal\MapField
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. |
↳ outputs |
array|Google\Protobuf\Internal\MapField
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. |
↳ feature_attributions_schema_uri |
string
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. |
↳ latent_space_source |
string
Name of the source to generate embeddings for example based explanations. |
getInputs
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.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\MapField | |
setInputs
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.
| Parameter | |
|---|---|
| Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getOutputs
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.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\MapField | |
setOutputs
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.
| Parameter | |
|---|---|
| Name | Description |
var |
array|Google\Protobuf\Internal\MapField
|
| Returns | |
|---|---|
| Type | Description |
$this | |
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.
| Returns | |
|---|---|
| Type | Description |
string | |
setFeatureAttributionsSchemaUri
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getLatentSpaceSource
Name of the source to generate embeddings for example based explanations.
| Returns | |
|---|---|
| Type | Description |
string | |
setLatentSpaceSource
Name of the source to generate embeddings for example based explanations.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |