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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ExplanationMetadata::OutputMetadata.
Metadata of the prediction output to be explained.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#display_name_mapping_key
def display_name_mapping_key() -> ::String-
(::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.
#display_name_mapping_key=
def display_name_mapping_key=(value) -> ::String-
value (::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.
-
(::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.
#index_display_name_mapping
def index_display_name_mapping() -> ::Google::Protobuf::Value-
(::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.
#index_display_name_mapping=
def index_display_name_mapping=(value) -> ::Google::Protobuf::Value-
value (::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.
-
(::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.
#output_tensor_name
def output_tensor_name() -> ::String- (::String) — Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.
#output_tensor_name=
def output_tensor_name=(value) -> ::String- value (::String) — Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.
- (::String) — Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.