A deconvolution layer in a network definition.
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#include <NvInfer.h>
A deconvolution layer in a network definition.
The output size is defined using the formula set by INetworkDefinition::setDeconvolutionOutputDimensionsFormula().
virtual Weights nvinfer1::IDeconvolutionLayer::getBiasWeights |
( |
| ) |
const |
|
pure virtual |
virtual DimsHW nvinfer1::IDeconvolutionLayer::getKernelSize |
( |
| ) |
const |
|
pure virtual |
virtual Weights nvinfer1::IDeconvolutionLayer::getKernelWeights |
( |
| ) |
const |
|
pure virtual |
Get the kernel weights for the deconvolution.
- See Also
- setNbGroups()
virtual int nvinfer1::IDeconvolutionLayer::getNbGroups |
( |
| ) |
const |
|
pure virtual |
Set the number of groups for a deconvolution.
- See Also
- setNbGroups()
virtual int nvinfer1::IDeconvolutionLayer::getNbOutputMaps |
( |
| ) |
const |
|
pure virtual |
Get the number of output feature maps for the deconvolution.
- See Also
- setNbOutputMaps()
virtual DimsHW nvinfer1::IDeconvolutionLayer::getPadding |
( |
| ) |
const |
|
pure virtual |
virtual DimsHW nvinfer1::IDeconvolutionLayer::getStride |
( |
| ) |
const |
|
pure virtual |
Get the stride of the deconvolution.
Default: (1,1)
virtual void nvinfer1::IDeconvolutionLayer::setBiasWeights |
( |
Weights |
weights | ) |
|
|
pure virtual |
Set the bias weights for the deconvolution.
Bias is optional. To omit bias, set the count value of the weights structure to zero.
The bias is applied per-feature-map, so the number of weights (if non-zero) must be equal to the number of output feature maps.
- See Also
- getBiasWeights()
virtual void nvinfer1::IDeconvolutionLayer::setKernelSize |
( |
DimsHW |
kernelSize | ) |
|
|
pure virtual |
virtual void nvinfer1::IDeconvolutionLayer::setKernelWeights |
( |
Weights |
weights | ) |
|
|
pure virtual |
Set the kernel weights for the deconvolution.
The weights are specified as a contiguous array in CKRS
order, where C
the number of input channels, K
the number of output feature maps, and R
and S
are the height and width of the filter.
- See Also
- getWeights()
virtual void nvinfer1::IDeconvolutionLayer::setNbGroups |
( |
int |
nbGroups | ) |
|
|
pure virtual |
Set the number of groups for a deconvolution.
The input tensor channels are divided into nbGroups
groups, and a deconvolution 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
- See Also
- getNbGroups()
virtual void nvinfer1::IDeconvolutionLayer::setNbOutputMaps |
( |
int |
nbOutputMaps | ) |
|
|
pure virtual |
Set the number of output feature maps for the deconvolution.
- See Also
- getNbOutputMaps()
virtual void nvinfer1::IDeconvolutionLayer::setPadding |
( |
DimsHW |
padding | ) |
|
|
pure virtual |
Set the padding of the deconvolution.
The input will be zero-padded by this number of elements in the height and width directions. Padding is symmetric.
Default: (0,0)
- See Also
- getPadding()
virtual void nvinfer1::IDeconvolutionLayer::setStride |
( |
DimsHW |
stride | ) |
|
|
pure virtual |
Get the stride of the deconvolution.
- See Also
- setStride()
The documentation for this class was generated from the following file: