Trait MetricRegistration 

pub trait MetricRegistration<M>: Sized
where
    M: LearnerModel,
{
    // Required method
    fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>;
}

Trait to fake variadic generics.

Required Methods

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

Register the metrics.

Dyn Compatibility

This trait is not dyn compatible.

In older versions of Rust, dyn compatibility was called "object safety".

Implementations on Foreign Types

impl<M1, M2, M3, M4, M5, M6, M> MetricRegistration<M> for (M1, M2, M3, M4, M5, M6)

where M: LearnerModel, <M as TrainStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input> + Adaptor<<M4 as Metric>::Input> + Adaptor<<M5 as Metric>::Input> + Adaptor<<M6 as Metric>::Input>, <M as InferenceStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input> + Adaptor<<M4 as Metric>::Input> + Adaptor<<M5 as Metric>::Input> + Adaptor<<M6 as Metric>::Input>, M1: Metric + Numeric + 'static, M2: Metric + Numeric + 'static, M3: Metric + Numeric + 'static, M4: Metric + Numeric + 'static, M5: Metric + Numeric + 'static, M6: Metric + Numeric + 'static,

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

impl<M1, M2, M3, M4, M5, M> MetricRegistration<M> for (M1, M2, M3, M4, M5)

where M: LearnerModel, <M as TrainStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input> + Adaptor<<M4 as Metric>::Input> + Adaptor<<M5 as Metric>::Input>, <M as InferenceStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input> + Adaptor<<M4 as Metric>::Input> + Adaptor<<M5 as Metric>::Input>, M1: Metric + Numeric + 'static, M2: Metric + Numeric + 'static, M3: Metric + Numeric + 'static, M4: Metric + Numeric + 'static, M5: Metric + Numeric + 'static,

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

impl<M1, M2, M3, M4, M> MetricRegistration<M> for (M1, M2, M3, M4)

where M: LearnerModel, <M as TrainStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input> + Adaptor<<M4 as Metric>::Input>, <M as InferenceStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input> + Adaptor<<M4 as Metric>::Input>, M1: Metric + Numeric + 'static, M2: Metric + Numeric + 'static, M3: Metric + Numeric + 'static, M4: Metric + Numeric + 'static,

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

impl<M1, M2, M3, M> MetricRegistration<M> for (M1, M2, M3)

where M: LearnerModel, <M as TrainStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input>, <M as InferenceStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input> + Adaptor<<M3 as Metric>::Input>, M1: Metric + Numeric + 'static, M2: Metric + Numeric + 'static, M3: Metric + Numeric + 'static,

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

impl<M1, M2, M> MetricRegistration<M> for (M1, M2)

where M: LearnerModel, <M as TrainStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input>, <M as InferenceStep>::Output: Adaptor<<M1 as Metric>::Input> + Adaptor<<M2 as Metric>::Input>, M1: Metric + Numeric + 'static, M2: Metric + Numeric + 'static,

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

impl<M1, M> MetricRegistration<M> for (M1,)

where M: LearnerModel, <M as TrainStep>::Output: Adaptor<<M1 as Metric>::Input>, <M as InferenceStep>::Output: Adaptor<<M1 as Metric>::Input>, M1: Metric + Numeric + 'static,

fn register(self, builder: SupervisedTraining<M>) -> SupervisedTraining<M>

Implementors