Struct LocalResponseNorm 

pub struct LocalResponseNorm { /* private fields */ }

Applies Local Response Normalization as described in ImageNet Classification with Deep Convolutional Neural Networks.

Y = X / (k + (alpha / size) * sum(X^2))^beta

Where the sum is computed over a sliding window of size channels.

For odd size, the window is centered on each channel position. For even size, the window uses asymmetric padding and includes the current channel plus one extra channel on the positive side.

Should be created using LocalResponseNormConfig.

Implementations

impl LocalResponseNorm

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

Applies Local Response Normalization on the input tensor.

Shapes

• input: [N, C, D1, D2, ..., Dk] (rank >= 3)
• output: same shape as input

Panics

Panics if the input tensor rank is less than 3.

Trait Implementations

impl Clone for LocalResponseNorm

fn clone(&self) -> LocalResponseNorm

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for LocalResponseNorm

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

Formats the value using the given formatter.

impl Display for LocalResponseNorm

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

Formats the value using the given formatter.

impl Module for LocalResponseNorm

fn visit<V>(&self, _visitor: &mut V)

where V: ModuleVisitor,

Visit each parameter and module-owned control value with a visitor.

fn map<M>(self, _mapper: &mut M) -> LocalResponseNorm

where M: ModuleMapper,

Map each parameter and module-owned control value with a mapper.

fn to_device(self, _: &Device) -> LocalResponseNorm

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

fn fork(self, _: &Device) -> LocalResponseNorm

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

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

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

fn materialize(self) -> LocalResponseNorm

Fold parameter reparameterizations into their effective values and remove them.

fn valid(&self) -> LocalResponseNorm

Returns a validation snapshot without autodiff or active training flags.

fn train(self) -> LocalResponseNorm

Enables autodiff and restores configured training state throughout the module.

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

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

fn set_require_grad(self, require_grad: bool) -> Self

Set whether every floating-point tensor parameter in the module tree requires gradients.

fn set_require_grad_group(self, group: ParamGroup, require_grad: bool) -> Self

Set whether matched floating-point tensor parameters require gradients.

fn no_grad(self) -> Self

Disable gradients for every floating-point tensor parameter in the module tree.

fn freeze(self) -> Self

Freeze the whole module tree.

fn unfreeze(self) -> Self

Unfreeze the whole module tree.

fn freeze_group(self, group: ParamGroup) -> Self

Freeze every module-owned value in the given group, leaving the rest of the module untouched.

fn unfreeze_group(self, group: ParamGroup) -> Self

Unfreeze every module-owned value in the given group, leaving the rest of the module untouched.

fn num_params(&self) -> usize

Get the number of parameters the module has, including all of its sub-modules, without initializing the ones not initialized yet.

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

Quantize the weights of the module.

fn quantize_weights_group( self, quantizer: &mut Quantizer, group: ParamGroup, ) -> Self

Quantize the weights of the given parameter group.

fn apply_reparameterization<R>(self, reparameterizer: R) -> Self

where Self: Sized, R: Reparameterizer,

Attach reparameterizations using the given Reparameterizer.

fn apply_lora(self, lora: Lora) -> Self

where Self: Sized,

Attach LoRA adapters to the module’s 2-D weights, freezing all base tensor parameters.

fn apply_qlora(self, qlora: QLora) -> Self

where Self: Sized,

Apply QLoRA to the module: quantize the (frozen) base tensor parameters and attach trainable LoRA adapters to 2-D weights.

fn into_record(self) -> ModuleRecord

where Self: Sized,

Collect this module’s tensor parameters into a ModuleRecord.

fn into_record_group(self, group: ParamGroup) -> ModuleRecord

where Self: Sized,

Collect the tensor parameters group names into a ModuleRecord.

fn try_load_record(self, record: ModuleRecord) -> Result<Self, RecordError>

where Self: Sized,

Apply a ModuleRecord to this module, returning the loaded module.

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

where Self: Sized,

Apply a ModuleRecord to this module, consuming and returning it.

fn save_file<P>(self, path: P) -> Result<(), RecordError>

where P: AsRef<Path>, Self: Sized,

Save this module’s parameters to a burnpack file on disk.

fn load_file<P>(self, path: P) -> Self

where P: AsRef<Path>, Self: Sized,

Load this module’s parameters from a burnpack file on disk, returning the loaded module.

fn try_load_file<P>(self, path: P) -> Result<Self, RecordError>

where P: AsRef<Path>, Self: Sized,

Fallible variant of load_file.

impl ModuleDisplay for LocalResponseNorm

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.

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

Formats the module with provided display settings.

impl ModuleDisplayDefault for LocalResponseNorm

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.