Struct google_api_proto::google::cloud::aiplatform::v1beta1::EvaluatedAnnotation

pub struct EvaluatedAnnotation {
    pub type: i32,
    pub predictions: Vec<Value>,
    pub ground_truths: Vec<Value>,
    pub data_item_payload: Option<Value>,
    pub evaluated_data_item_view_id: String,
    pub explanations: Vec<EvaluatedAnnotationExplanation>,
    pub error_analysis_annotations: Vec<ErrorAnalysisAnnotation>,
}

True positive, false positive, or false negative.

EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of annotationSpec dimension.

Fields

type: i32

Output only. Type of the EvaluatedAnnotation.

predictions: Vec<Value>

Output only. The model predicted annotations.

For true positive, there is one and only one prediction, which matches the only one ground truth annotation in [ground_truths][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.ground_truths].

For false positive, there is one and only one prediction, which doesn’t match any ground truth annotation of the corresponding [data_item_view_id][EvaluatedAnnotation.data_item_view_id].

For false negative, there are zero or more predictions which are similar to the only ground truth annotation in [ground_truths][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.ground_truths] but not enough for a match.

The schema of the prediction is stored in [ModelEvaluation.annotation_schema_uri][]

ground_truths: Vec<Value>

Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on.

For true positive, there is one and only one ground truth annotation, which matches the only prediction in [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions].

For false positive, there are zero or more ground truth annotations that are similar to the only prediction in [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions], but not enough for a match.

For false negative, there is one and only one ground truth annotation, which doesn’t match any predictions created by the model.

The schema of the ground truth is stored in [ModelEvaluation.annotation_schema_uri][]

data_item_payload: Option<Value>

Output only. The data item payload that the Model predicted this EvaluatedAnnotation on.

evaluated_data_item_view_id: String

Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on [data_item_payload][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.data_item_payload].

explanations: Vec<EvaluatedAnnotationExplanation>

Explanations of [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions]. Each element of the explanations indicates the explanation for one explanation Method.

The attributions list in the [EvaluatedAnnotationExplanation.explanation][google.cloud.aiplatform.v1beta1.EvaluatedAnnotationExplanation.explanation] object corresponds to the [predictions][google.cloud.aiplatform.v1beta1.EvaluatedAnnotation.predictions] list. For example, the second element in the attributions list explains the second element in the predictions list.

error_analysis_annotations: Vec<ErrorAnalysisAnnotation>

Annotations of model error analysis results.

Implementations

impl EvaluatedAnnotation

pub fn type(&self) -> EvaluatedAnnotationType

Returns the enum value of type, or the default if the field is set to an invalid enum value.

pub fn set_type(&mut self, value: EvaluatedAnnotationType)

Sets type to the provided enum value.

Trait Implementations

impl Clone for EvaluatedAnnotation

fn clone(&self) -> EvaluatedAnnotation

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for EvaluatedAnnotation

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for EvaluatedAnnotation

fn default() -> Self

Returns the “default value” for a type.

impl Message for EvaluatedAnnotation

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for EvaluatedAnnotation

fn eq(&self, other: &EvaluatedAnnotation) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for EvaluatedAnnotation