nvinfer1::INormalizationLayer Class Reference

A normalization layer in a network definition. More...

#include <NvInfer.h>

Inheritance diagram for nvinfer1::INormalizationLayer:

Public Member Functions
void	setEpsilon (float eps) noexcept
	Set the epsilon value used for the normalization calculation. More...
float	getEpsilon () const noexcept
	Get the epsilon value used for the normalization calculation. More...
void	setAxes (uint32_t axesMask) noexcept
	Set the reduction axes for the normalization calculation. More...
uint32_t	getAxes () const noexcept
	Get the axes value used for the normalization calculation. More...
void	setNbGroups (int64_t nbGroups) noexcept
	Set the number of groups used to split the channels in the normalization calculation. More...
int64_t	getNbGroups () const noexcept
	Get the number of groups used to split the channels for the normalization calculation. More...
void	setComputePrecision (DataType type) noexcept
	Set the compute precision of this layer. More...
DataType	getComputePrecision () const noexcept
	Get the compute precision of this layer. More...
Public Member Functions inherited from nvinfer1::ILayer
LayerType	getType () const noexcept
	Return the type of a layer. More...
void	setName (char const *name) noexcept
	Set the name of a layer. More...
char const *	getName () const noexcept
	Return the name of a layer. More...
int32_t	getNbInputs () const noexcept
	Get the number of inputs of a layer. More...
ITensor *	getInput (int32_t index) const noexcept
	Get the layer input corresponding to the given index. More...
int32_t	getNbOutputs () const noexcept
	Get the number of outputs of a layer. More...
ITensor *	getOutput (int32_t index) const noexcept
	Get the layer output corresponding to the given index. More...
void	setInput (int32_t index, ITensor &tensor) noexcept
	Replace an input of this layer with a specific tensor. More...
void	setPrecision (DataType dataType) noexcept
	Set the preferred or required computational precision of this layer in a weakly-typed network. More...
DataType	getPrecision () const noexcept
	get the computational precision of this layer More...
bool	precisionIsSet () const noexcept
	whether the computational precision has been set for this layer More...
void	resetPrecision () noexcept
	reset the computational precision for this layer More...
void	setOutputType (int32_t index, DataType dataType) noexcept
	Set the output type of this layer in a weakly-typed network. More...
DataType	getOutputType (int32_t index) const noexcept
	get the output type of this layer More...
bool	outputTypeIsSet (int32_t index) const noexcept
	whether the output type has been set for this layer More...
void	resetOutputType (int32_t index) noexcept
	reset the output type for this layer More...
void	setMetadata (char const *metadata) noexcept
	Set the metadata for this layer. More...
char const *	getMetadata () const noexcept
	Get the metadata of the layer. More...

Protected Member Functions
virtual	~INormalizationLayer () noexcept=default
Protected Member Functions inherited from nvinfer1::ILayer
virtual	~ILayer () noexcept=default
Protected Member Functions inherited from nvinfer1::INoCopy
	INoCopy ()=default
virtual	~INoCopy ()=default
	INoCopy (INoCopy const &other)=delete
INoCopy &	operator= (INoCopy const &other)=delete
	INoCopy (INoCopy &&other)=delete
INoCopy &	operator= (INoCopy &&other)=delete

Protected Attributes
apiv::VNormalizationLayer *	mImpl
Protected Attributes inherited from nvinfer1::ILayer
apiv::VLayer *	mLayer

Detailed Description

A normalization layer in a network definition.

The normalization layer performs the following operation:

X - input Tensor Y - output Tensor S - scale Tensor B - bias Tensor

Y = (X - Mean(X, axes)) / Sqrt(Variance(X) + epsilon) * S + B

Where Mean(X, axes) is a reduction over a set of axes, and Variance(X) = Mean((X - Mean(X, axes)) ^ 2, axes).

Warning

Do not inherit from this class, as doing so will break forward-compatibility of the API and ABI.

Constructor & Destructor Documentation

~INormalizationLayer()

virtual nvinfer1::INormalizationLayer::~INormalizationLayer ( )

protectedvirtualdefaultnoexcept

Member Function Documentation

getAxes()

uint32_t nvinfer1::INormalizationLayer::getAxes ( ) const

inlinenoexcept

Get the axes value used for the normalization calculation.

Returns

The axes used for the normalization calculation.

getComputePrecision()

DataType nvinfer1::INormalizationLayer::getComputePrecision ( ) const

inlinenoexcept

Get the compute precision of this layer.

Returns

The datatype used for the compute precision of this layer.

getEpsilon()

float nvinfer1::INormalizationLayer::getEpsilon ( ) const

inlinenoexcept

Get the epsilon value used for the normalization calculation.

Returns

The epsilon value used for the normalization calculation.

getNbGroups()

int64_t nvinfer1::INormalizationLayer::getNbGroups ( ) const

inlinenoexcept

Get the number of groups used to split the channels for the normalization calculation.

Returns

The number of groups used to split the channel used for the normalization calculation.

setAxes()

void nvinfer1::INormalizationLayer::setAxes ( uint32_t  axesMask )

inlinenoexcept

Set the reduction axes for the normalization calculation.

Parameters

axesMask

The axes used for the normalization calculation.

setComputePrecision()

void nvinfer1::INormalizationLayer::setComputePrecision ( DataType  type )

inlinenoexcept

Set the compute precision of this layer.

Parameters

type	The datatype used for the compute precision of this layer.

The method is used to avoid overflow errors by controlling the normalization computation in mixed precision mode. The compute precision defaults to DataType::kFLOAT32. To override this default, use this method to set the desired compute precision.

For a weakly typed network:

• Method setOutputType() can still be called to control the output data type.
• Method setPrecision() can still be called. The input data is cast to that precision before being cast to the compute precision.

Strongly typed network rejects calls to this method since the compute precision is typically controlled by casting the input tensors to the desired type.

Only DataType::kFLOAT32 and DataType::kHALF are valid types for type.

setEpsilon()

void nvinfer1::INormalizationLayer::setEpsilon ( float  eps )

inlinenoexcept

Set the epsilon value used for the normalization calculation.

The default value of eps is 1e-5F.

Parameters

eps	The epsilon value used for the normalization calculation.

setNbGroups()

void nvinfer1::INormalizationLayer::setNbGroups ( int64_t  nbGroups )

inlinenoexcept

Set the number of groups used to split the channels in the normalization calculation.

The input tensor channels are divided into nbGroups groups, and normalization is performed per group. The channel dimension is considered to be the second dimension in a [N, C, H, W, ...] formatted tensor.

The default nbGroups is 1.

Warning

It is an error to set nbGroups to a value that does not evenly divide into the number of channels of the input tensor.

When nbGroups is != 1, it is expected that the provided axesMask will have all bits corresponding to dimensions after the channel dimension set to 1, with all other bits set to 0.

Parameters

nbGroups

The number of groups to split the channels into for the normalization calculation.

Member Data Documentation

mImpl

apiv::VNormalizationLayer* nvinfer1::INormalizationLayer::mImpl

protected

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The documentation for this class was generated from the following file:

• NvInfer.h