TensorRT 10.0.0
nvinfer1::IConvolutionLayer Class Reference

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

#include <NvInfer.h>

Inheritance diagram for nvinfer1::IConvolutionLayer:
nvinfer1::ILayer nvinfer1::INoCopy

Public Member Functions

void setNbOutputMaps (int64_t nbOutputMaps) noexcept
 Set the number of output maps for the convolution. More...
 
int64_t getNbOutputMaps () const noexcept
 Get the number of output maps for the convolution. More...
 
void setNbGroups (int64_t nbGroups) noexcept
 Set the number of groups for a convolution. More...
 
int64_t getNbGroups () const noexcept
 Get the number of groups of the convolution. More...
 
void setKernelWeights (Weights weights) noexcept
 Set the kernel weights for the convolution. More...
 
Weights getKernelWeights () const noexcept
 Get the kernel weights of the convolution. More...
 
void setBiasWeights (Weights weights) noexcept
 Set the bias weights for the convolution. More...
 
Weights getBiasWeights () const noexcept
 Get the bias weights for the convolution. More...
 
void setPrePadding (Dims const &padding) noexcept
 Set the multi-dimension pre-padding of the convolution. More...
 
Dims getPrePadding () const noexcept
 Get the pre-padding. More...
 
void setPostPadding (Dims const &padding) noexcept
 Set the multi-dimension post-padding of the convolution. More...
 
Dims getPostPadding () const noexcept
 Get the post-padding. More...
 
void setPaddingMode (PaddingMode paddingMode) noexcept
 Set the padding mode. More...
 
PaddingMode getPaddingMode () const noexcept
 Get the padding mode. More...
 
void setKernelSizeNd (Dims const &kernelSize) noexcept
 Set the multi-dimension kernel size of the convolution. More...
 
Dims getKernelSizeNd () const noexcept
 Get the multi-dimension kernel size of the convolution. More...
 
void setStrideNd (Dims const &stride) noexcept
 Set the multi-dimension stride of the convolution. More...
 
Dims getStrideNd () const noexcept
 Get the multi-dimension stride of the convolution. More...
 
void setPaddingNd (Dims const &padding) noexcept
 Set the multi-dimension padding of the convolution. More...
 
Dims getPaddingNd () const noexcept
 Get the multi-dimension padding of the convolution. More...
 
void setDilationNd (Dims const &dilation) noexcept
 Set the multi-dimension dilation of the convolution. More...
 
Dims getDilationNd () const noexcept
 Get the multi-dimension dilation of the convolution. More...
 
void setInput (int32_t index, ITensor &tensor) noexcept
 Append or replace an input of this layer with a specific tensor. 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...
 
ITensorgetInput (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...
 
ITensorgetOutput (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 ~IConvolutionLayer () 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
 
INoCopyoperator= (INoCopy const &other)=delete
 
 INoCopy (INoCopy &&other)=delete
 
INoCopyoperator= (INoCopy &&other)=delete
 

Protected Attributes

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

Detailed Description

A convolution layer in a network definition.

This layer performs a correlation operation between 3-dimensional filter with a 4-dimensional tensor to produce another 4-dimensional tensor.

An optional bias argument is supported, which adds a per-channel constant to each value in the output.

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

Constructor & Destructor Documentation

◆ ~IConvolutionLayer()

virtual nvinfer1::IConvolutionLayer::~IConvolutionLayer ( )
protectedvirtualdefaultnoexcept

Member Function Documentation

◆ getBiasWeights()

Weights nvinfer1::IConvolutionLayer::getBiasWeights ( ) const
inlinenoexcept

Get the bias weights for the convolution.

See also
setBiasWeights()

◆ getDilationNd()

Dims nvinfer1::IConvolutionLayer::getDilationNd ( ) const
inlinenoexcept

Get the multi-dimension dilation of the convolution.

See also
setDilation()

◆ getKernelSizeNd()

Dims nvinfer1::IConvolutionLayer::getKernelSizeNd ( ) const
inlinenoexcept

Get the multi-dimension kernel size of the convolution.

See also
setKernelSizeNd()

◆ getKernelWeights()

Weights nvinfer1::IConvolutionLayer::getKernelWeights ( ) const
inlinenoexcept

Get the kernel weights of the convolution.

See also
setKernelWeights()

◆ getNbGroups()

int64_t nvinfer1::IConvolutionLayer::getNbGroups ( ) const
inlinenoexcept

Get the number of groups of the convolution.

See also
setNbGroups()

◆ getNbOutputMaps()

int64_t nvinfer1::IConvolutionLayer::getNbOutputMaps ( ) const
inlinenoexcept

Get the number of output maps for the convolution.

See also
setNbOutputMaps()

◆ getPaddingMode()

PaddingMode nvinfer1::IConvolutionLayer::getPaddingMode ( ) const
inlinenoexcept

Get the padding mode.

Default: kEXPLICIT_ROUND_DOWN

See also
setPaddingMode()

◆ getPaddingNd()

Dims nvinfer1::IConvolutionLayer::getPaddingNd ( ) const
inlinenoexcept

Get the multi-dimension padding of the convolution.

If the padding is asymmetric, the pre-padding is returned.

See also
setPaddingNd()

◆ getPostPadding()

Dims nvinfer1::IConvolutionLayer::getPostPadding ( ) const
inlinenoexcept

Get the post-padding.

See also
setPostPadding()

◆ getPrePadding()

Dims nvinfer1::IConvolutionLayer::getPrePadding ( ) const
inlinenoexcept

Get the pre-padding.

See also
setPrePadding()

◆ getStrideNd()

Dims nvinfer1::IConvolutionLayer::getStrideNd ( ) const
inlinenoexcept

Get the multi-dimension stride of the convolution.

See also
setStrideNd()

◆ setBiasWeights()

void nvinfer1::IConvolutionLayer::setBiasWeights ( Weights  weights)
inlinenoexcept

Set the bias weights for the convolution.

Bias is optional. To omit bias, set the count value of the weights structure to zero.

The bias is applied per-channel, so the number of weights (if non-zero) must be equal to the number of output feature maps.

See also
getBiasWeights()

◆ setDilationNd()

void nvinfer1::IConvolutionLayer::setDilationNd ( Dims const &  dilation)
inlinenoexcept

Set the multi-dimension dilation of the convolution.

Default: (1, 1, ..., 1)

If executing this layer on DLA, only support 2D padding, both height and width must be in the range [1,32].

See also
getDilation()

◆ setInput()

void nvinfer1::ILayer::setInput ( int32_t  index,
ITensor tensor 
)
inlinenoexcept

Append or replace an input of this layer with a specific tensor.

Parameters
indexthe index of the input to modify.
tensorthe new input tensor

The indices are as follows:

Input 0 is the input activation tensor. Input 1 is the kernel tensor. If used, the kernel weights parameter must be set to empty weights. Input 2 is the bias tensor. If used, the bias parameter must be set to empty weights.

See also
getKernelWeights(), setKernelWeights(), getBiasWeights(), setBiasWeights()

◆ setKernelSizeNd()

void nvinfer1::IConvolutionLayer::setKernelSizeNd ( Dims const &  kernelSize)
inlinenoexcept

Set the multi-dimension kernel size of the convolution.

If executing this layer on DLA, only support 2D kernel size, both height and width of kernel size must be in the range [1,32].

See also
getKernelSizeNd()

◆ setKernelWeights()

void nvinfer1::IConvolutionLayer::setKernelWeights ( Weights  weights)
inlinenoexcept

Set the kernel weights for the convolution.

The weights are specified as a contiguous array in GKCRS order, where G is the number of groups, K the number of output feature maps, C the number of input channels, and R and S are the height and width of the filter.

See also
getKernelWeights()

◆ setNbGroups()

void nvinfer1::IConvolutionLayer::setNbGroups ( int64_t  nbGroups)
inlinenoexcept

Set the number of groups for a convolution.

The input tensor channels are divided into nbGroups groups, and a convolution is executed for each group, using a filter per group. The results of the group convolutions are concatenated to form the output.

Note
When using groups in int8 mode, the size of the groups (i.e. the channel count divided by the group count) must be a multiple of 4 for both input and output.

Default: 1

If executing this layer on DLA, the max number of groups is 8192.

See also
getNbGroups()

◆ setNbOutputMaps()

void nvinfer1::IConvolutionLayer::setNbOutputMaps ( int64_t  nbOutputMaps)
inlinenoexcept

Set the number of output maps for the convolution.

If executing this layer on DLA, the number of output maps must be in the range [1,8192].

See also
getNbOutputMaps()

◆ setPaddingMode()

void nvinfer1::IConvolutionLayer::setPaddingMode ( PaddingMode  paddingMode)
inlinenoexcept

Set the padding mode.

Padding mode takes precedence if both setPaddingMode and setPre/PostPadding are used.

Default: kEXPLICIT_ROUND_DOWN

See also
getPaddingMode()

◆ setPaddingNd()

void nvinfer1::IConvolutionLayer::setPaddingNd ( Dims const &  padding)
inlinenoexcept

Set the multi-dimension padding of the convolution.

The input will be zero-padded by this number of elements in each dimension. Padding is symmetric.

Default: (0, 0, ..., 0)

If executing this layer on DLA, only support 2D padding, both height and width of padding must be in the range [0,31], and the padding must be less than the kernel size.

See also
getPaddingNd() setPadding() getPadding()

◆ setPostPadding()

void nvinfer1::IConvolutionLayer::setPostPadding ( Dims const &  padding)
inlinenoexcept

Set the multi-dimension post-padding of the convolution.

The end of the input will be zero-padded by this number of elements in each dimension.

Default: (0, 0, ..., 0)

If executing this layer on DLA, only support 2D padding, both height and width of padding must be in the range [0,31], and the padding must be less than the kernel size.

See also
getPostPadding()

◆ setPrePadding()

void nvinfer1::IConvolutionLayer::setPrePadding ( Dims const &  padding)
inlinenoexcept

Set the multi-dimension pre-padding of the convolution.

The start of the input will be zero-padded by this number of elements in each dimension.

Default: (0, 0, ..., 0)

If executing this layer on DLA, only support 2D padding, both height and width of padding must be in the range [0,31], and the padding must be less than the kernel size.

See also
getPrePadding()

◆ setStrideNd()

void nvinfer1::IConvolutionLayer::setStrideNd ( Dims const &  stride)
inlinenoexcept

Set the multi-dimension stride of the convolution.

Default: (1, 1, ..., 1)

If executing this layer on DLA, only support 2D stride, both height and width of stride must be in the range [1,8].

See also
getStrideNd()

Member Data Documentation

◆ mImpl

apiv::VConvolutionLayer* nvinfer1::IConvolutionLayer::mImpl
protected

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

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