Google Cloud Ai Platform V1 Client - Class OutputMetadata (1.35.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class OutputMetadata.

Metadata of the prediction output to be explained.

Generated from protobuf message google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata

Namespace

Google \ Cloud \ AIPlatform \ V1 \ ExplanationMetadata

Methods

__construct

Constructor.

Parameters
Name	Description
`data`	`array` Optional. Data for populating the Message object.
`↳ index_display_name_mapping`	`Google\Protobuf\Value` Static mapping between the index and display name. Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non-deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index.
`↳ display_name_mapping_key`	`string` Specify a field name in the prediction to look for the display name. Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output.
`↳ output_tensor_name`	`string` Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.

getIndexDisplayNameMapping

Static mapping between the index and display name.

Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non-deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index.

Returns
Type	Description
`Google\Protobuf\Value\|null`

hasIndexDisplayNameMapping

setIndexDisplayNameMapping

Static mapping between the index and display name.

Parameter
Name	Description
`var`	`Google\Protobuf\Value`

Returns
Type	Description
`$this`

getDisplayNameMappingKey

Specify a field name in the prediction to look for the display name.

Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output.

Returns
Type	Description
`string`

hasDisplayNameMappingKey

setDisplayNameMappingKey