org.bytedeco.tensorrt.nvinfer

Class IDeconvolutionLayer

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.tensorrt.nvinfer.INoCopy

org.bytedeco.tensorrt.nvinfer.ILayer

org.bytedeco.tensorrt.nvinfer.IDeconvolutionLayer

All Implemented Interfaces:

AutoCloseable

@Namespace(value="nvinfer1")
 @NoOffset
 @Properties(inherit=nvinfer.class)
public class IDeconvolutionLayer
extends ILayer

\class IDeconvolutionLayer \brief A deconvolution layer in a network definition. \warning Do not inherit from this class, as doing so will break forward-compatibility of the API and ABI.

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
IDeconvolutionLayer(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
Weights	getBiasWeights() \brief Get the bias weights for the deconvolution.
Dims32	getDilationNd() \brief Get the multi-dimension dilation of the deconvolution.
DimsHW	getKernelSize() Deprecated. Superseded by getKernelSizeNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0
Dims32	getKernelSizeNd() \brief Get the multi-dimension kernel size of the deconvolution.
Weights	getKernelWeights() \brief Get the kernel weights for the deconvolution.
int	getNbGroups() \brief Get the number of groups for a deconvolution.
int	getNbOutputMaps() \brief Get the number of output feature maps for the deconvolution.
DimsHW	getPadding() Deprecated. Superseded by getPaddingNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0
nvinfer.PaddingMode	getPaddingMode() \brief Get the padding mode.
Dims32	getPaddingNd() \brief Get the multi-dimension padding of the deconvolution.
Dims32	getPostPadding() \brief Get the padding.
Dims32	getPrePadding() \brief Get the pre-padding.
DimsHW	getStride() Deprecated. Superseded by getStrideNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0
Dims32	getStrideNd() \brief Get the multi-dimension stride of the deconvolution.
void	setBiasWeights(Weights weights) \brief Set the bias weights for the deconvolution.
void	setDilationNd(Dims32 dilation) \brief Set the multi-dimension dilation of the deconvolution.
void	setKernelSize(DimsHW kernelSize) Deprecated. Superseded by setKernelSizeNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0
void	setKernelSizeNd(Dims32 kernelSize) \brief Set the multi-dimension kernel size of the deconvolution.
void	setKernelWeights(Weights weights) \brief Set the kernel weights for the deconvolution.
void	setNbGroups(int nbGroups) \brief Set the number of groups for a deconvolution.
void	setNbOutputMaps(int nbOutputMaps) \brief Set the number of output feature maps for the deconvolution.
void	setPadding(DimsHW padding) Deprecated. Superseded by setPaddingNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0
void	setPaddingMode(int paddingMode)
void	setPaddingMode(nvinfer.PaddingMode paddingMode) \brief Set the padding mode.
void	setPaddingNd(Dims32 padding) \brief Set the multi-dimension padding of the deconvolution.
void	setPostPadding(Dims32 padding) \brief Set the multi-dimension post-padding of the deconvolution.
void	setPrePadding(Dims32 padding) \brief Set the multi-dimension pre-padding of the deconvolution.
void	setStride(DimsHW stride) Deprecated. Superseded by setStrideNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0
void	setStrideNd(Dims32 stride) \brief Set the multi-dimension stride of the deconvolution.

Methods inherited from class org.bytedeco.tensorrt.nvinfer.ILayer

getInput, getName, getNbInputs, getNbOutputs, getOutput, getOutputType, getPrecision, getType, outputTypeIsSet, precisionIsSet, resetOutputType, resetPrecision, setInput, setName, setName, setOutputType, setOutputType, setPrecision, setPrecision

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

IDeconvolutionLayer

public IDeconvolutionLayer(Pointer p)

Pointer cast constructor. Invokes Pointer(Pointer).

Method Detail

setKernelSize

@Deprecated
 @NoException(value=true)
public void setKernelSize(@ByVal
                                                                  DimsHW kernelSize)

Deprecated. Superseded by setKernelSizeNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0

\brief 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 [1,32], 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].

See Also:

getKernelSize()

getKernelSize

@Deprecated
 @ByVal
 @NoException(value=true)
public DimsHW getKernelSize()

Deprecated. Superseded by getKernelSizeNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0

\brief Get the HW kernel size of the deconvolution.

See Also:

setKernelSize()

setNbOutputMaps

@NoException(value=true)
public void setNbOutputMaps(int nbOutputMaps)

\brief 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].

See Also:

getNbOutputMaps()

getNbOutputMaps

@NoException(value=true)
public int getNbOutputMaps()

\brief Get the number of output feature maps for the deconvolution.

See Also:

setNbOutputMaps()

setStride

@Deprecated
 @NoException(value=true)
public void setStride(@ByVal
                                                              DimsHW stride)

Deprecated. Superseded by setStrideNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0

\brief Set the stride of the deconvolution. If executing this layer on DLA, there is one restriction: 1) 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].

See Also:

getStride()

getStride

@Deprecated
 @ByVal
 @NoException(value=true)
public DimsHW getStride()

Deprecated. Superseded by getStrideNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0

\brief Get the stride of the deconvolution. Default: (1,1)

setPadding

@Deprecated
 @NoException(value=true)
public void setPadding(@ByVal
                                                               DimsHW padding)

Deprecated. Superseded by setPaddingNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0

\brief Set the padding of the deconvolution. The output will be trimmed by this number of elements on each side in the height and width directions. 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) If executing this layer on DLA, both height and width of padding must be 0.

See Also:

getPadding()

getPadding

@Deprecated
 @ByVal
 @NoException(value=true)
public DimsHW getPadding()

Deprecated. Superseded by getPaddingNd. Deprecated prior to TensorRT 8.0 and will be removed in 9.0

\brief Get the padding of the deconvolution. Default: (0, 0)

See Also:

setPadding()

setNbGroups

@NoException(value=true)
public void setNbGroups(int nbGroups)

\brief Set the number of groups for a deconvolution. The input tensor channels are divided into \p 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 \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()

getNbGroups

@NoException(value=true)
public int getNbGroups()

\brief Get the number of groups for a deconvolution.

See Also:

setNbGroups()

setKernelWeights

@NoException(value=true)
public void setKernelWeights(@ByVal
                                                       Weights weights)

\brief Set the kernel weights for the deconvolution. The weights are specified as a contiguous array in \p CKRS order, where \p C the number of input channels, \p K the number of output feature maps, and \p R and \p S are the height and width of the filter.

See Also:

getWeights()

getKernelWeights

@ByVal
 @NoException(value=true)
public Weights getKernelWeights()

\brief Get the kernel weights for the deconvolution.

See Also:

setNbGroups()

setBiasWeights

@NoException(value=true)
public void setBiasWeights(@ByVal
                                                     Weights weights)

\brief 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()

getBiasWeights

@ByVal
 @NoException(value=true)
public Weights getBiasWeights()

\brief Get the bias weights for the deconvolution.

See Also:

getBiasWeights()

setPrePadding

@NoException(value=true)
public void setPrePadding(@ByVal @Cast(value="nvinfer1::Dims*")
                                                    Dims32 padding)

\brief 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.

See Also:

getPrePadding()

getPrePadding

@ByVal
 @Cast(value="nvinfer1::Dims*")
 @NoException(value=true)
public Dims32 getPrePadding()

\brief Get the pre-padding.

See Also:

setPrePadding()

setPostPadding

@NoException(value=true)
public void setPostPadding(@ByVal @Cast(value="nvinfer1::Dims*")
                                                     Dims32 padding)

\brief 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.

See Also:

getPostPadding()

getPostPadding

@ByVal
 @Cast(value="nvinfer1::Dims*")
 @NoException(value=true)
public Dims32 getPostPadding()

\brief Get the padding.

See Also:

setPostPadding()

setPaddingMode

@NoException(value=true)
public void setPaddingMode(nvinfer.PaddingMode paddingMode)

\brief Set the padding mode. Padding mode takes precedence if both setPaddingMode and setPre/PostPadding are used. Default: kEXPLICIT_ROUND_DOWN

See Also:

getPaddingMode()

setPaddingMode

@NoException(value=true)
public void setPaddingMode(@Cast(value="nvinfer1::PaddingMode")
                                                     int paddingMode)

getPaddingMode

@NoException(value=true)
public nvinfer.PaddingMode getPaddingMode()

\brief Get the padding mode. Default: kEXPLICIT_ROUND_DOWN

See Also:

setPaddingMode()

setKernelSizeNd

@NoException(value=true)
public void setKernelSizeNd(@ByVal @Cast(value="nvinfer1::Dims*")
                                                      Dims32 kernelSize)

\brief 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].

See Also:

setKernelSize() getKernelSize()

getKernelSizeNd

@ByVal
 @Cast(value="nvinfer1::Dims*")
 @NoException(value=true)
public Dims32 getKernelSizeNd()

\brief Get the multi-dimension kernel size of the deconvolution.

See Also:

setKernelSizeNd()

setStrideNd

@NoException(value=true)
public void setStrideNd(@ByVal @Cast(value="nvinfer1::Dims*")
                                                  Dims32 stride)

\brief 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].

See Also:

setStride() getStride()

getStrideNd

@ByVal
 @Cast(value="nvinfer1::Dims*")
 @NoException(value=true)
public Dims32 getStrideNd()

\brief Get the multi-dimension stride of the deconvolution.

See Also:

setStrideNd()

setPaddingNd

@NoException(value=true)
public void setPaddingNd(@ByVal @Cast(value="nvinfer1::Dims*")
                                                   Dims32 padding)

\brief 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.

See Also:

setPadding() getPadding()

getPaddingNd

@ByVal
 @Cast(value="nvinfer1::Dims*")
 @NoException(value=true)
public Dims32 getPaddingNd()

\brief Get the multi-dimension padding of the deconvolution. If the padding is asymmetric, the pre-padding is returned.

See Also:

setPaddingNd()

setDilationNd

@NoException(value=true)
public void setDilationNd(@ByVal @Cast(value="nvinfer1::Dims*")
                                                    Dims32 dilation)

\brief Set the multi-dimension dilation of the deconvolution. Default: (1, 1, ..., 1)

See Also:

getDilationNd()

getDilationNd

@ByVal
 @Cast(value="nvinfer1::Dims*")
 @NoException(value=true)
public Dims32 getDilationNd()

\brief Get the multi-dimension dilation of the deconvolution.

See Also:

setDilationNd()