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
Methods
__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.
Generated from protobuf field repeated .google.protobuf.Value input_baselines = 1;
| 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.
Generated from protobuf field repeated .google.protobuf.Value input_baselines = 1;
| 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.
Generated from protobuf field string input_tensor_name = 2;
| 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.
Generated from protobuf field string input_tensor_name = 2;
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getEncoding
Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
Generated from protobuf field .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
| Returns | |
|---|---|
| Type | Description |
int | |
setEncoding
Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
Generated from protobuf field .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
| Parameter | |
|---|---|
| Name | Description |
var |
int
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getModality
Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
Generated from protobuf field string modality = 4;
| Returns | |
|---|---|
| Type | Description |
string | |
setModality
Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
Generated from protobuf field string modality = 4;
| 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.
Generated from protobuf field .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
| 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.
Generated from protobuf field .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
| 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.
Generated from protobuf field string indices_tensor_name = 6;
| 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.
Generated from protobuf field string indices_tensor_name = 6;
| 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.
Generated from protobuf field string dense_shape_tensor_name = 7;
| 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.
Generated from protobuf field string dense_shape_tensor_name = 7;
| 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.
Generated from protobuf field repeated string index_feature_mapping = 8;
| 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.
Generated from protobuf field repeated string index_feature_mapping = 8;
| 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.
Generated from protobuf field string encoded_tensor_name = 9;
| 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.
Generated from protobuf field string encoded_tensor_name = 9;
| 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.
Generated from protobuf field repeated .google.protobuf.Value encoded_baselines = 10;
| 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.
Generated from protobuf field repeated .google.protobuf.Value encoded_baselines = 10;
| Parameter | |
|---|---|
| Name | Description |
var |
array<Google\Protobuf\Value>
|
| Returns | |
|---|---|
| Type | Description |
$this | |
getVisualization
Visualization configurations for image explanation.
Generated from protobuf field .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
| Returns | |
|---|---|
| Type | Description |
Google\Cloud\AIPlatform\V1\ExplanationMetadata\InputMetadata\Visualization|null | |
hasVisualization
clearVisualization
setVisualization
Visualization configurations for image explanation.
Generated from protobuf field .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
| 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.
Generated from protobuf field string group_name = 12;
| 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.
Generated from protobuf field string group_name = 12;
| Parameter | |
|---|---|
| Name | Description |
var |
string
|
| Returns | |
|---|---|
| Type | Description |
$this | |