Struct BatchNorm 

pub struct BatchNorm { /* private fields */ }

Batch Normalization layer

Normalizes the input across the channel dimension for NHWC tensors.

Implementations

impl BatchNorm

pub fn new(num_features: usize) -> Self

Create a new BatchNorm layer with default initialization

• gamma initialized to 1.0
• beta initialized to 0.0
• running_mean initialized to 0.0
• running_var initialized to 1.0

pub fn with_epsilon(num_features: usize, epsilon: f32) -> Self

Create BatchNorm with custom epsilon

pub fn set_params(&mut self, gamma: Vec<f32>, beta: Vec<f32>) -> CnnResult<()>

Set the learned parameters (gamma, beta)

pub fn set_running_stats( &mut self, mean: Vec<f32>, var: Vec<f32>, ) -> CnnResult<()>

Set the running statistics (mean, var)

pub fn num_features(&self) -> usize

Get the number of features (channels)

pub fn gamma(&self) -> &[f32]

Get a reference to gamma

pub fn beta(&self) -> &[f32]

Get a reference to beta

pub fn running_mean(&self) -> &[f32]

Get a reference to running mean

pub fn running_var(&self) -> &[f32]

Get a reference to running variance

Trait Implementations

impl Clone for BatchNorm

fn clone(&self) -> BatchNorm

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for BatchNorm

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

Formats the value using the given formatter.

impl Layer for BatchNorm

fn forward(&self, input: &Tensor) -> CnnResult<Tensor>

Perform the forward pass

fn name(&self) -> &'static str

Get the layer name

fn num_params(&self) -> usize

Get the number of parameters