TensorRT 10.0.1
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A deconvolution layer in a network definition. More...
#include <NvInfer.h>
Public Member Functions | |
void | setNbOutputMaps (int64_t nbOutputMaps) noexcept |
Set the number of output feature maps for the deconvolution. More... | |
int64_t | getNbOutputMaps () const noexcept |
Get the number of output feature maps for the deconvolution. More... | |
void | setNbGroups (int64_t nbGroups) noexcept |
Set the number of groups for a deconvolution. More... | |
int64_t | getNbGroups () const noexcept |
Get the number of groups for a deconvolution. More... | |
void | setKernelWeights (Weights weights) noexcept |
Set the kernel weights for the deconvolution. More... | |
Weights | getKernelWeights () const noexcept |
Get the kernel weights for the deconvolution. More... | |
void | setBiasWeights (Weights weights) noexcept |
Set the bias weights for the deconvolution. More... | |
Weights | getBiasWeights () const noexcept |
Get the bias weights for the deconvolution. More... | |
void | setPrePadding (Dims const &padding) noexcept |
Set the multi-dimension pre-padding of the deconvolution. More... | |
Dims | getPrePadding () const noexcept |
Get the pre-padding. More... | |
void | setPostPadding (Dims const &padding) noexcept |
Set the multi-dimension post-padding of the deconvolution. More... | |
Dims | getPostPadding () const noexcept |
Get the 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 deconvolution. More... | |
Dims | getKernelSizeNd () const noexcept |
Get the multi-dimension kernel size of the deconvolution. More... | |
void | setStrideNd (Dims const &stride) noexcept |
Set the multi-dimension stride of the deconvolution. More... | |
Dims | getStrideNd () const noexcept |
Get the multi-dimension stride of the deconvolution. More... | |
void | setPaddingNd (Dims const &padding) noexcept |
Set the multi-dimension padding of the deconvolution. More... | |
Dims | getPaddingNd () const noexcept |
Get the multi-dimension padding of the deconvolution. More... | |
void | setDilationNd (Dims const &dilation) noexcept |
Set the multi-dimension dilation of the deconvolution. More... | |
Dims | getDilationNd () const noexcept |
Get the multi-dimension dilation of the deconvolution. 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... | |
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 | ~IDeconvolutionLayer () 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::VDeconvolutionLayer * | mImpl |
Protected Attributes inherited from nvinfer1::ILayer | |
apiv::VLayer * | mLayer |
A deconvolution layer in a network definition.
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protectedvirtualdefaultnoexcept |
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inlinenoexcept |
Get the bias weights for the deconvolution.
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inlinenoexcept |
Get the multi-dimension dilation of the deconvolution.
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inlinenoexcept |
Get the multi-dimension kernel size of the deconvolution.
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inlinenoexcept |
Get the kernel weights for the deconvolution.
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inlinenoexcept |
Get the number of groups for a deconvolution.
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inlinenoexcept |
Get the number of output feature maps for the deconvolution.
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inlinenoexcept |
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inlinenoexcept |
Get the multi-dimension padding of the deconvolution.
If the padding is asymmetric, the pre-padding is returned.
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inlinenoexcept |
Get the padding.
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inlinenoexcept |
Get the pre-padding.
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inlinenoexcept |
Get the multi-dimension stride of the deconvolution.
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inlinenoexcept |
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.
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inlinenoexcept |
Set the multi-dimension dilation of the deconvolution.
Default: (1, 1, ..., 1)
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inlinenoexcept |
Append or replace an input of this layer with a specific tensor.
index | the index of the input to modify. |
tensor | the new input tensor |
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.
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inlinenoexcept |
Set the multi-dimension kernel size of the deconvolution.
If executing this layer on DLA, there are ttwo restrictions: 1) Only 2D Kernel is supported. 2) Kernel height and width must be in the range [1,32] or the combinations of [64, 96, 128] in one dimension and 1 in the other dimensions, i.e. [1x64] or [64x1] are valid, but not [64x64].
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inlinenoexcept |
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.
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inlinenoexcept |
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.
If executing this layer on DLA, nbGroups must be one
Default: 1
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inlinenoexcept |
Set the number of output feature maps for the deconvolution.
If executing this layer on DLA, the number of output maps must be in the range [1,8192].
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inlinenoexcept |
Set the padding mode.
Padding mode takes precedence if both setPaddingMode and setPre/PostPadding are used.
Default: kEXPLICIT_ROUND_DOWN
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inlinenoexcept |
Set the multi-dimension padding of the deconvolution.
The output will be trimmed by this number of elements on both sides of every dimension. In other words, it resembles the inverse of a convolution layer with this padding size. Padding is symmetric, and negative padding is not supported.
Default: (0, 0, ..., 0)
If executing this layer on DLA, padding must be 0.
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inlinenoexcept |
Set the multi-dimension post-padding of the deconvolution.
The output will be trimmed by this number of elements on the end of every dimension. In other words, it resembles the inverse of a convolution layer with this padding size. Negative padding is not supported.
Default: (0, 0, ..., 0)
If executing this layer on DLA, padding must be 0.
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inlinenoexcept |
Set the multi-dimension pre-padding of the deconvolution.
The output will be trimmed by this number of elements on the start of every dimension. In other words, it resembles the inverse of a convolution layer with this padding size. Negative padding is not supported.
Default: (0, 0, ..., 0)
If executing this layer on DLA, padding must be 0.
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inlinenoexcept |
Set the multi-dimension stride of the deconvolution.
Default: (1, 1, ..., 1)
If executing this layer on DLA, there are two restrictions: 1) Only 2D Stride is supported. 2) Stride height and width must be in the range [1,32] or the combinations of [64, 96, 128] in one dimension and 1 in the other dimensions, i.e. [1x64] or [64x1] are valid, but not [64x64].
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protected |
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