Struct Softmax

pub struct Softmax(pub f32);

A softmax activation layer with no trainable parameters.

Tuple Fields

0: f32

Trait Implementations

impl Clone for Softmax

fn clone(&self) -> Softmax

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Softmax

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

Formats the value using the given formatter.

impl Default for Softmax

fn default() -> Self

Returns the “default value” for a type.

impl LoadableModule for Softmax

fn save( &self, _path: String, _dict: &mut HashMap<String, Vec<f64>>, ) -> Result<(), LoadSaveError>

Saves the parameters to the given dictionary.

fn load( &mut self, _path: String, _dict: &HashMap<String, Vec<f64>>, ) -> Result<(), LoadSaveError>

Loads the parameters from the given dictionary.

impl<E: Float, const I: usize> Module<[E; I]> for Softmax

type Output = [E; I]

The type that this unit produces given Input.

fn forward(&self, x: &[E; I]) -> Result<Self::Output, Error>

impl ResetParams for Softmax

fn rand_params<RNG: Rng>( &mut self, _rng: &mut RNG, _scale: f32, ) -> Result<(), Error>

Sensibly initializes the learnable parameters of some module.

impl<E: Float, const I: usize> RevModule<[E; I]> for Softmax

type SelfGrads = ()

The type describing gradients with respect to the modules’ own parameters.

fn reverse( &self, inputs: &[E; I], grads_wrt_output: &[E; I], ) -> ([E; I], Self::SelfGrads)

Returns the gradients with respect to the input, and the gradients with respect to any internal parameters.

fn apply( &mut self, _applyer: &mut impl GradApplyer, _updates: Self::SelfGrads, ) -> Result<(), Error>

Applies a gradient update step: adding product of the provided gradients and the scalar to the parameters.

impl VisualizableUnit for Softmax

const KIND: &'static str = "softmax"

type Params = ()

fn params(&self) -> &Self::Params