Struct burn_core::nn::BatchNorm

pub struct BatchNorm<B: Backend, const D: usize> { /* private fields */ }

Applies Batch Normalization over a tensor as described in the paper Batch Normalization

Y = norm(X) * γ + β

Implementations

impl<const D: usize, B: Backend> BatchNorm<B, D>

pub fn forward<const DI: usize>(&self, input: Tensor<B, DI>) -> Tensor<B, DI>

Applies the forward pass on the input tensor.

Shapes

• input: [batch_size, channels, ...]
• output: [batch_size, channels, ...]

Trait Implementations

impl<B, const D: usize> ADModule<B> for BatchNorm<B, D>where B: ADBackend + Backend,

type InnerModule = BatchNorm<<B as ADBackend>::InnerBackend, D>

fn valid(&self) -> Self::InnerModule

Get the same module, but on the inner backend without auto-differentiation.

impl<B: Backend, const D: usize> Clone for BatchNorm<B, D>

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<B: Debug + Backend, const D: usize> Debug for BatchNorm<B, D>

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

Formats the value using the given formatter.

impl<B: Backend, const D: usize> Display for BatchNorm<B, D>

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

Formats the value using the given formatter.

impl<B: Backend, const D: usize> Module<B> for BatchNorm<B, D>

type Record = BatchNormRecord<B, D>

Type to save and load the module.

fn load_record(self, record: Self::Record) -> Self

Load the module state from a record.

fn into_record(self) -> Self::Record

Convert the module into a record containing the state.

fn num_params(&self) -> usize

Get the number of parameters the module has, including all of its sub-modules.

fn visit<V: ModuleVisitor<B>>(&self, visitor: &mut V)

Visit each tensor in the module with a visitor.

fn map<M: ModuleMapper<B>>(self, mapper: &mut M) -> Self

Map each tensor in the module with a mapper.

fn devices(&self) -> Vec<B::Device>

Get the device list of the module and all of its sub-modules.

fn fork(self, device: &B::Device) -> Self

Fork the module and all of its sub-modules to the given device.

fn to_device(self, device: &B::Device) -> Self

Move the module and all of its sub-modules to the given device.

fn no_grad(self) -> Self

Each tensor in the module tree will not require grad.