Struct KLDivergence 

pub struct KLDivergence;

KL Divergence computations

Implementations

impl KLDivergence

pub fn gaussian_to_unit(gaussian: &DiagonalGaussian) -> f32

KL(N(mu, sigma^2) || N(0, 1)) = 0.5 * sum(exp(log_var) + mu^2 - 1 - log_var)

pub fn gaussian_to_unit_arrays(mean: &[f32], log_var: &[f32]) -> f32

KL(N(mu, sigma^2) || N(0, 1)) from separate arrays

pub fn gaussian_to_gaussian(q: &DiagonalGaussian, p: &DiagonalGaussian) -> f32

KL(N(mu1, sigma1^2) || N(mu2, sigma2^2)) = 0.5 * sum(log(var2/var1) + (var1 + (mu1-mu2)^2)/var2 - 1)

pub fn categorical(p: &[f32], q: &[f32]) -> f32

KL divergence between categorical distributions KL(p || q) = sum(p * log(p/q))

pub fn jensen_shannon(p: &[f32], q: &[f32]) -> f32

Symmetric KL (Jensen-Shannon divergence approximation) JS(p, q) ≈ 0.5 * (KL(p || m) + KL(q || m)) where m = (p+q)/2

Trait Implementations

impl Clone for KLDivergence

fn clone(&self) -> KLDivergence

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for KLDivergence

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

Formats the value using the given formatter.