Enum engram::loss::Loss

pub enum Loss {
    BCE,
    MSE,
}

Loss functions that can be used to train a neural network.

Variants

BCE

Binary cross-entropy.

MSE

Mean squared error.

Implementations

impl Loss

pub fn loss(&self, predictions: &Tensor, targets: &Tensor) -> Tensor

pub fn grad(&self, predictions: &Tensor, targets: &Tensor) -> Tensor

Trait Implementations

impl Clone for Loss

fn clone(&self) -> Loss

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Loss

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

Formats the value using the given formatter.

impl Hash for Loss

fn hash<__H: Hasher>(&self, state: &mut __H)

Feeds this value into the given Hasher.

fn hash_slice<H>(data: &[Self], state: &mut H)

where H: Hasher, Self: Sized,

Feeds a slice of this type into the given Hasher.

impl PartialEq for Loss

fn eq(&self, other: &Loss) -> 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 Copy for Loss

impl StructuralPartialEq for Loss