Struct GradL2Norm

pub struct GradL2Norm;

Trait Implementations

impl<G> Metric<&GradientDescent<G>> for GradL2Norm

type Output = f64

The type of elements recorded by the metric. For a delta of last vs current, this might be an n-dimentional vector. It typically needs to be an Owned type, rather than a reference.

fn observe_opt(&mut self, algo: &GradientDescent<G>) -> Option<Self::Output>

Similar to observe except None is returned instead of f64::NAN to indicate not enough data collected. Useful if you like

fn observe(&mut self, x: Input) -> f64

where Self::Output: Into<f64>,

Records the value, and return the calculated metric. If there are not enough samples to calculate the metric, f64::NAN is returned, which will always compare false. So a tolerance check observe(x) < 0.0001 will fail until enough samples have been collected. If you don’t like NANs, then Metric::observe_opt is your friend.