Struct google_api_proto::google::cloud::aiplatform::v1beta1::ModelEvaluation

pub struct ModelEvaluation {
    pub name: String,
    pub display_name: String,
    pub metrics_schema_uri: String,
    pub metrics: Option<Value>,
    pub create_time: Option<Timestamp>,
    pub slice_dimensions: Vec<String>,
    pub model_explanation: Option<ModelExplanation>,
    pub explanation_specs: Vec<ModelEvaluationExplanationSpec>,
    pub metadata: Option<Value>,
    pub bias_configs: Option<BiasConfig>,
}

A collection of metrics calculated by comparing Model’s predictions on all of the test data against annotations from the test data.

Fields

name: String

Output only. The resource name of the ModelEvaluation.

display_name: String

The display name of the ModelEvaluation.

metrics_schema_uri: String

Points to a YAML file stored on Google Cloud Storage describing the [metrics][google.cloud.aiplatform.v1beta1.ModelEvaluation.metrics] of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 Schema Object.

metrics: Option<Value>

Evaluation metrics of the Model. The schema of the metrics is stored in [metrics_schema_uri][google.cloud.aiplatform.v1beta1.ModelEvaluation.metrics_schema_uri]

create_time: Option<Timestamp>

Output only. Timestamp when this ModelEvaluation was created.

slice_dimensions: Vec<String>

All possible [dimensions][google.cloud.aiplatform.v1beta1.ModelEvaluationSlice.Slice.dimension] of ModelEvaluationSlices. The dimensions can be used as the filter of the [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluationSlices] request, in the form of slice.dimension = <dimension>.

model_explanation: Option<ModelExplanation>

Aggregated explanation metrics for the Model’s prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models.

explanation_specs: Vec<ModelEvaluationExplanationSpec>

Describes the values of [ExplanationSpec][google.cloud.aiplatform.v1beta1.ExplanationSpec] that are used for explaining the predicted values on the evaluated data.

metadata: Option<Value>

The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of “pipeline_job_id”, “evaluation_dataset_type”, “evaluation_dataset_path”, “row_based_metrics_path”.

bias_configs: Option<BiasConfig>

Specify the configuration for bias detection.

Trait Implementations

impl Clone for ModelEvaluation

fn clone(&self) -> ModelEvaluation

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for ModelEvaluation

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

Formats the value using the given formatter.

impl Default for ModelEvaluation

fn default() -> Self

Returns the “default value” for a type.

impl Message for ModelEvaluation

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 ModelEvaluation

fn eq(&self, other: &ModelEvaluation) -> 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 ModelEvaluation