TensorRT
5.1.3.4
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A convolution layer in a network definition. More...
#include <NvInfer.h>
Public Member Functions | |
virtual void | setKernelSize (DimsHW kernelSize)=0 |
Set the HW kernel size of the convolution. More... | |
virtual DimsHW | getKernelSize () const =0 |
Get the HW kernel size of the convolution. More... | |
virtual void | setNbOutputMaps (int nbOutputMaps)=0 |
Set the number of output maps for the convolution. More... | |
virtual int | getNbOutputMaps () const =0 |
Get the number of output maps for the convolution. More... | |
virtual void | setStride (DimsHW stride)=0 |
Get the stride of the convolution. More... | |
virtual DimsHW | getStride () const =0 |
Get the stride of the convolution. | |
virtual void | setPadding (DimsHW padding)=0 |
Set the padding of the convolution. More... | |
virtual DimsHW | getPadding () const =0 |
Get the padding of the convolution. If the padding is asymmetric, the pre-padding is returned. More... | |
virtual void | setNbGroups (int nbGroups)=0 |
Set the number of groups for a convolution. More... | |
virtual int | getNbGroups () const =0 |
Set the number of groups for a convolution. More... | |
virtual void | setKernelWeights (Weights weights)=0 |
Set the kernel weights for the convolution. More... | |
virtual Weights | getKernelWeights () const =0 |
Get the kernel weights for the convolution. More... | |
virtual void | setBiasWeights (Weights weights)=0 |
Set the bias weights for the convolution. More... | |
virtual Weights | getBiasWeights () const =0 |
Get the bias weights for the convolution. More... | |
virtual void | setDilation (DimsHW dims)=0 |
Set the dilation for a convolution. More... | |
virtual DimsHW | getDilation () const =0 |
Get the dilation for a convolution. More... | |
virtual void | setPrePadding (Dims padding)=0 |
Set the pre-padding. More... | |
virtual Dims | getPrePadding () const =0 |
Get the pre-padding. More... | |
virtual void | setPostPadding (Dims padding)=0 |
Set the post-padding. More... | |
virtual Dims | getPostPadding () const =0 |
Get the post-padding. More... | |
virtual void | setPaddingMode (PaddingMode paddingMode)=0 |
Set the padding mode. More... | |
virtual PaddingMode | getPaddingMode () const =0 |
Get the padding mode. More... | |
Public Member Functions inherited from nvinfer1::ILayer | |
virtual LayerType | getType () const =0 |
Return the type of a layer. More... | |
virtual void | setName (const char *name)=0 |
Set the name of a layer. More... | |
virtual const char * | getName () const =0 |
Return the name of a layer. More... | |
virtual int | getNbInputs () const =0 |
Get the number of inputs of a layer. | |
virtual ITensor * | getInput (int index) const =0 |
Get the layer input corresponding to the given index. More... | |
virtual int | getNbOutputs () const =0 |
Get the number of outputs of a layer. | |
virtual ITensor * | getOutput (int index) const =0 |
Get the layer output corresponding to the given index. More... | |
virtual void | setInput (int index, ITensor &tensor)=0 |
replace an input of this layer with a specific tensor More... | |
virtual void | setPrecision (DataType dataType)=0 |
Set the computational precision of this layer. More... | |
virtual DataType | getPrecision () const =0 |
get the computational precision of this layer More... | |
virtual bool | precisionIsSet () const =0 |
whether the computational precision has been set for this layer More... | |
virtual void | resetPrecision ()=0 |
reset the computational precision for this layer More... | |
virtual void | setOutputType (int index, DataType dataType)=0 |
Set the output type of this layer. More... | |
virtual DataType | getOutputType (int index) const =0 |
get the output type of this layer More... | |
virtual bool | outputTypeIsSet (int index) const =0 |
whether the output type has been set for this layer More... | |
virtual void | resetOutputType (int index)=0 |
reset the output type for this layer More... | |
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.
The HW output size of the convolution is set according to the INetworkCustomDimensions
set in INetworkDefinition::setCustomConvolutionDimensions().
An optional bias argument is supported, which adds a per-channel constant to each value in the output.
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pure virtual |
Get the bias weights for the convolution.
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pure virtual |
Get the dilation for a convolution.
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pure virtual |
Get the HW kernel size of the convolution.
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pure virtual |
Get the kernel weights for the convolution.
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pure virtual |
Set the number of groups for a convolution.
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pure virtual |
Get the number of output maps for the convolution.
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pure virtual |
Get the padding of the convolution. If the padding is asymmetric, the pre-padding is returned.
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pure virtual |
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pure virtual |
Get the post-padding.
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pure virtual |
Get the pre-padding.
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pure virtual |
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.
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pure virtual |
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pure virtual |
Set the HW kernel size of the convolution.
If executing this layer on DLA, both height and width of kernel size must be in the range [1,16].
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pure virtual |
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.
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pure virtual |
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.
Default: 1
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pure virtual |
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].
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pure virtual |
Set the padding of the convolution.
The input will be zero-padded by this number of elements in the height and width directions. Padding is symmetric.
Default: (0,0)
If executing this layer on DLA, both height and width of padding must be in the range [0,15].
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pure virtual |
Set the padding mode.
Padding mode gets precedence if both setPaddingMode and setPre/PostPadding are used.
Default: kEXPLICIT_ROUND_DOWN
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pure virtual |
Set the post-padding.
The end of the input will be zero-padded by this number of elements in the height and width directions.
Default: (0,0)
If executing this layer on DLA, both height and width of padding must be in the range [0,15].
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pure virtual |
Set the pre-padding.
The start of input will be zero-padded by this number of elements in the height and width directions.
Default: 0
If executing this layer on DLA, both height and width of padding must be in the range [0,15].
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pure virtual |
Get the stride of the convolution.
Default: (1,1)
If executing this layer on DLA, both height and width of stride must be in the range [1,8].