Struct burn_core::nn::LayerNorm

pub struct LayerNorm<B: Backend> { /* private fields */ }

Applies Layer Normalization over an input tensor as described in the paper Layer Normalization.

Y = norm(X) * γ + β

Implementations

impl<B: Backend> LayerNorm<B>

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

Applies the forward pass on the input tensor.

Shapes

• input: [..., any, d_model]
• output: [..., any, d_model]

Trait Implementations

impl<B> ADModule<B> for LayerNorm<B>where B: ADBackend + Backend,

type InnerModule = LayerNorm<<B as ADBackend>::InnerBackend>

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

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

impl<B: Backend> Clone for LayerNorm<B>

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> Debug for LayerNorm<B>

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

Formats the value using the given formatter.

impl<B: Backend> Display for LayerNorm<B>

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

Formats the value using the given formatter.

impl<B: Backend> Module<B> for LayerNorm<B>

type Record = LayerNormRecord<B>

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.