Enum Normalization

#[non_exhaustive]
pub enum Normalization<B>
where
    B: Backend,
{
    Batch(BatchNorm<B>),
    Group(GroupNorm<B>),
    Instance(InstanceNorm<B>),
    Layer(LayerNorm<B>),
    Rms(RmsNorm<B>),
}

Normalization Layer Wrapper

Provides support for built-in burn::nn::norm norm layers:

• Normalization::Batch - BatchNorm
• Normalization::Group - GroupNorm
• Normalization::Instance - InstanceNorm
• Normalization::Layer - LayerNorm
• Normalization::Rms - RmsNorm

The enum is non-exhaustive, to prepare for future additions.

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

Batch(BatchNorm<B>)

BatchNorm layer.

Group(GroupNorm<B>)

GroupNorm layer.

Instance(InstanceNorm<B>)

[‘InstanceNorm’] layer.

Layer(LayerNorm<B>)

LayerNorm layer.

Rms(RmsNorm<B>)

[‘RmsNorm’] layer.

Implementations

impl<B> Normalization<B>

where B: Backend,

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

Applies normalization to a tensor.

The normalization contract depends upon the wrapped norm layer; but all norm layers assume an input of at least rank 2; and produce an output of the same rank and shape.

pub fn num_features(&self) -> usize

Get the number of features.

Trait Implementations

impl<B> AutodiffModule<B> for Normalization<B>

where B: Backend + AutodiffBackend, <B as AutodiffBackend>::InnerBackend: Backend,

type InnerModule = Normalization<<B as AutodiffBackend>::InnerBackend>

Inner module without auto-differentiation.

fn valid(&self) -> <Normalization<B> as AutodiffModule<B>>::InnerModule

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

impl<B> Clone for Normalization<B>

where B: Backend,

fn clone(&self) -> Normalization<B>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<B> Debug for Normalization<B>

where B: Debug + Backend,

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

Formats the value using the given formatter.

impl<B> Display for Normalization<B>

where B: Backend,

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

Formats the value using the given formatter.

impl<B> From<BatchNorm<B>> for Normalization<B>

where B: Backend,

fn from(layer: BatchNorm<B>) -> Normalization<B>

Converts to this type from the input type.

impl<B> From<GroupNorm<B>> for Normalization<B>

where B: Backend,

fn from(layer: GroupNorm<B>) -> Normalization<B>

Converts to this type from the input type.

impl<B> From<InstanceNorm<B>> for Normalization<B>

where B: Backend,

fn from(layer: InstanceNorm<B>) -> Normalization<B>

Converts to this type from the input type.

impl<B> From<LayerNorm<B>> for Normalization<B>

where B: Backend,

fn from(layer: LayerNorm<B>) -> Normalization<B>

Converts to this type from the input type.

impl<B> From<RmsNorm<B>> for Normalization<B>

where B: Backend,

fn from(layer: RmsNorm<B>) -> Normalization<B>

Converts to this type from the input type.

impl<B> Module<B> for Normalization<B>

where B: Backend,

type Record = NormalizationRecord<B>

Type to save and load the module.

fn load_record( self, record: <Normalization<B> as Module<B>>::Record, ) -> Normalization<B>

Load the module state from a record.

fn into_record(self) -> <Normalization<B> as Module<B>>::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<Visitor>(&self, visitor: &mut Visitor)

where Visitor: ModuleVisitor<B>,

Visit each tensor parameter in the module with a visitor.

fn map<Mapper>(self, mapper: &mut Mapper) -> Normalization<B>

where Mapper: ModuleMapper<B>,

Map each tensor parameter in the module with a mapper.

fn collect_devices( &self, devices: Vec<<B as Backend>::Device>, ) -> Vec<<B as Backend>::Device>

Return all the devices found in the underneath module tree added to the given vector without duplicates.

fn to_device(self, device: &<B as Backend>::Device) -> Normalization<B>

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

fn fork(self, device: &<B as Backend>::Device) -> Normalization<B>

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

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

Return all the devices found in the underneath module tree without duplicates.

fn no_grad(self) -> Self

Each tensor in the module tree will not require grad.

fn save_file<FR, PB>( self, file_path: PB, recorder: &FR, ) -> Result<(), RecorderError>

where FR: FileRecorder<B>, PB: Into<PathBuf>,

Save the module to a file using the provided file recorder.

fn load_file<FR, PB>( self, file_path: PB, recorder: &FR, device: &<B as Backend>::Device, ) -> Result<Self, RecorderError>

where FR: FileRecorder<B>, PB: Into<PathBuf>,

Load the module from a file using the provided file recorder.

fn quantize_weights(self, quantizer: &mut Quantizer) -> Self

Quantize the weights of the module.

impl<B> ModuleDisplay for Normalization<B>

where B: Backend,

fn format(&self, passed_settings: DisplaySettings) -> String

Formats the module with provided display settings.

fn custom_settings(&self) -> Option<DisplaySettings>

Custom display settings for the module.

fn custom_content(&self, _content: Content) -> Option<Content>

Custom attributes for the module.

impl<B> ModuleDisplayDefault for Normalization<B>

where B: Backend,

fn content(&self, content: Content) -> Option<Content>

Attributes of the module used for display purposes.

fn num_params(&self) -> usize

Gets the number of the parameters of the module.