Struct TrainingOutcome 

pub struct TrainingOutcome {

    pub schema_version: u32,
    pub outcome_id: String,
    pub run_id: RunId,
    pub training_request_fingerprint: String,
    pub data_identities: Vec<TrainingDataIdentity>,
    pub selection_output_id: String,
    pub effective_plan: ExecutionPlan,
    pub effective_plan_fingerprint: String,
    pub selected_variant_id: VariantId,
    pub selected_variant_fingerprint: String,
    pub parameter_patches: Vec<ParameterPatch>,
    pub refit: TrainingRefitOutcome,
    pub score_set: ScoreSet,
    pub outputs: Vec<BoundTrainingOutput>,
    pub lineage: Vec<LineageRecord>,
    pub portable_prediction_caches: Option<BundlePredictionCachePayloadSet>,
    pub training_influence: TrainingInfluenceManifest,
    pub execution_bundle: ExecutionBundle,
    pub conformal_calibration: Option<ConformalCalibration>,
    pub conformal_calibration_replay: Option<TrainingReplayOutcome>,
    pub methods_hpo_resume_state: Option<MethodsHpoResumeState>,
    pub replayable_phases: Vec<Phase>,
    pub warnings: Vec<String>,
    pub diagnostics: BTreeMap<String, Value>,
    pub outcome_fingerprint: String,
}

Portable result of COMPILE/PLAN/FIT_CV/SELECT and optional REFIT.

Fields

schema_version: u32

outcome_id: String

run_id: RunId

training_request_fingerprint: String

data_identities: Vec<TrainingDataIdentity>

selection_output_id: String

effective_plan: ExecutionPlan

effective_plan_fingerprint: String

selected_variant_id: VariantId

selected_variant_fingerprint: String

parameter_patches: Vec<ParameterPatch>

refit: TrainingRefitOutcome

score_set: ScoreSet

outputs: Vec<BoundTrainingOutput>

lineage: Vec<LineageRecord>

portable_prediction_caches: Option<BundlePredictionCachePayloadSet>

training_influence: TrainingInfluenceManifest

execution_bundle: ExecutionBundle

conformal_calibration: Option<ConformalCalibration>

conformal_calibration_replay: Option<TrainingReplayOutcome>

Complete pre-calibration replay evidence. V2 calibration attachment retains this beside the derived quantiles so a loaded package can independently revalidate the replay/source/sample closure.

methods_hpo_resume_state: Option<MethodsHpoResumeState>

replayable_phases: Vec<Phase>

warnings: Vec<String>

diagnostics: BTreeMap<String, Value>

outcome_fingerprint: String

Implementations

impl TrainingOutcome

pub fn from_json(json: &str) -> Result<TrainingOutcome, DagMlError>

Strictly parse a self-fingerprinted W0 outcome without losing the JSON integer-versus-binary64 token distinction before verification.

pub fn compute_fingerprint(&self) -> Result<String, DagMlError>

pub fn data_identities_fingerprint(&self) -> Result<String, DagMlError>

pub fn execution_bundle_fingerprint(&self) -> Result<String, DagMlError>

pub fn to_reference(&self) -> Result<TrainingOutcomeRef, DagMlError>

Build the compact cross-link embedded by a portable predictor package.

pub fn to_portable_predictor_package( &self, package_id: impl Into<String>, fitted_artifact_mode: FittedArtifactMode, artifact_load_mode: ArtifactLoadMode, ) -> Result<PortablePredictorPackage, DagMlError>

Export a self-contained portable predictor package contract from this training outcome. Runtime handles are never serialized; host-sidecar artifacts are represented only by their signed artifact descriptors and must be resolved into process-local handles by PortablePredictorPackage::load_with.

pub fn validate(&self) -> Result<(), DagMlError>

Trait Implementations

impl Clone for TrainingOutcome

fn clone(&self) -> TrainingOutcome

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TrainingOutcome

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for TrainingOutcome

fn deserialize<__D>( __deserializer: __D, ) -> Result<TrainingOutcome, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for TrainingOutcome

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

Equality operator ==.

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

Inequality operator !=.

impl Serialize for TrainingOutcome

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for TrainingOutcome