Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class InputMetadata.
Metadata 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.
Generated from protobuf message google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata
Namespace
Google \ Cloud \ AIPlatform \ V1 \ ExplanationMetadataMethods
__construct
Constructor.
| Parameters | |
|---|---|
| Name | Description |
data |
array
Optional. Data for populating the Message object. |
↳ input_baselines |
array<Google\Protobuf\Value>
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. |
↳ input_tensor_name |
string
Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow. |
↳ encoding |
int
Defines how the feature is encoded into the input tensor. Defaults to IDENTITY. |
↳ modality |
string
Modality of the feature. Valid values are: numeric, image. Defaults to numeric. |
↳ feature_value_domain |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\FeatureValueDomain
The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized. |
↳ indices_tensor_name |
string
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. |
↳ dense_shape_tensor_name |
string
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. |
↳ index_feature_mapping |
array
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. |
↳ encoded_tensor_name |
string
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. |
↳ encoded_baselines |
array<Google\Protobuf\Value>
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. |
↳ visualization |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\Visualization
Visualization configurations for image explanation. |
↳ group_name |
string
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. |
getInputBaselines
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.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setInputBaselines
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.
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Protobuf\Value>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getInputTensorName
Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.
| Returns | |
|---|---|
| Type | Description |
string | |
setInputTensorName
Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getEncoding
Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
| Returns | |
|---|---|
| Type | Description |
int | |
setEncoding
Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
| Parameter | |
|---|---|
| Name | Description |
var |
int
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getModality
Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
| Returns | |
|---|---|
| Type | Description |
string | |
setModality
Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getFeatureValueDomain
The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\FeatureValueDomain|null | |
hasFeatureValueDomain
clearFeatureValueDomain
setFeatureValueDomain
The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\FeatureValueDomain
|
| Returns | |
|---|---|
| Type | Description |
$this | |
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.
| Returns | |
|---|---|
| Type | Description |
string | |
setIndicesTensorName
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
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.
| Returns | |
|---|---|
| Type | Description |
string | |
setDenseShapeTensorName
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getIndexFeatureMapping
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.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setIndexFeatureMapping
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string[]
|
| Returns | |
|---|---|
| Type | Description |
$this | |
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.
| Returns | |
|---|---|
| Type | Description |
string | |
setEncodedTensorName
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getEncodedBaselines
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.
| Returns | |
|---|---|
| Type | Description |
Google\Protobuf\Internal\RepeatedField | |
setEncodedBaselines
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.
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Protobuf\Value>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getVisualization
Visualization configurations for image explanation.
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\Visualization|null | |
hasVisualization
clearVisualization
setVisualization
Visualization configurations for image explanation.
| Parameter | |
|---|---|
| Name | Description |
var |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\Visualization
|
| Returns | |
|---|---|
| Type | Description |
$this | |
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.
| Returns | |
|---|---|
| Type | Description |
string | |
setGroupName
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.
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |