134 :
Dims2(height, width)
144 int&
h() {
return d[0]; }
151 int h()
const {
return d[0]; }
158 int&
w() {
return d[1]; }
165 int w()
const {
return d[1]; }
181 d[0] =
d[1] =
d[2] = 0;
227 :
Dims3(channels, height, width)
238 int&
c() {
return d[0]; }
245 int c()
const {
return d[0]; }
252 int&
h() {
return d[1]; }
259 int h()
const {
return d[1]; }
266 int&
w() {
return d[2]; }
273 int w()
const {
return d[2]; }
289 d[0] =
d[1] =
d[2] =
d[3] = 0;
300 Dims4(
int d0,
int d1,
int d2,
int d3)
338 DimsNCHW(
int batchSize,
int channels,
int height,
int width)
339 :
Dims4(batchSize, channels, height, width)
351 int&
n() {
return d[0]; }
358 int n()
const {
return d[0]; }
365 int&
c() {
return d[1]; }
372 int c()
const {
return d[1]; }
379 int&
h() {
return d[2]; }
386 int h()
const {
return d[2]; }
393 int&
w() {
return d[3]; }
400 int w()
const {
return d[3]; }
478 virtual void setName(
const char* name) TRTNOEXCEPT = 0;
487 virtual const char* getName()
const TRTNOEXCEPT = 0;
503 virtual void setDimensions(
Dims dimensions) TRTNOEXCEPT = 0;
513 virtual Dims getDimensions()
const TRTNOEXCEPT = 0;
534 virtual DataType getType()
const TRTNOEXCEPT = 0;
546 virtual bool setDynamicRange(
float min,
float max) TRTNOEXCEPT = 0;
555 TRT_DEPRECATED
virtual float getDynamicRange()
const TRTNOEXCEPT = 0;
560 virtual bool isNetworkInput()
const TRTNOEXCEPT = 0;
565 virtual bool isNetworkOutput()
const TRTNOEXCEPT = 0;
588 virtual void setBroadcastAcrossBatch(
bool broadcastAcrossBatch) TRTNOEXCEPT = 0;
601 virtual bool getBroadcastAcrossBatch()
const TRTNOEXCEPT = 0;
620 virtual void setLocation(
TensorLocation location) TRTNOEXCEPT = 0;
627 virtual bool dynamicRangeIsSet()
const TRTNOEXCEPT = 0;
632 virtual void resetDynamicRange() TRTNOEXCEPT = 0;
639 virtual float getDynamicRangeMin()
const TRTNOEXCEPT = 0;
646 virtual float getDynamicRangeMax()
const TRTNOEXCEPT = 0;
656 virtual void setAllowedFormats(
TensorFormats formats) TRTNOEXCEPT = 0;
666 virtual TensorFormats getAllowedFormats()
const TRTNOEXCEPT = 0;
678 virtual bool isShapeTensor()
const TRTNOEXCEPT = 0;
694 virtual bool isExecutionTensor()
const TRTNOEXCEPT = 0;
712 virtual LayerType getType()
const TRTNOEXCEPT = 0;
721 virtual void setName(
const char* name) TRTNOEXCEPT = 0;
729 virtual const char* getName()
const TRTNOEXCEPT = 0;
734 virtual int getNbInputs()
const TRTNOEXCEPT = 0;
744 virtual ITensor* getInput(
int index)
const TRTNOEXCEPT = 0;
749 virtual int getNbOutputs()
const TRTNOEXCEPT = 0;
757 virtual ITensor* getOutput(
int index)
const TRTNOEXCEPT = 0;
773 virtual void setInput(
int index,
ITensor& tensor) TRTNOEXCEPT = 0;
790 virtual void setPrecision(
DataType dataType) TRTNOEXCEPT = 0;
799 virtual DataType getPrecision()
const TRTNOEXCEPT = 0;
808 virtual bool precisionIsSet()
const TRTNOEXCEPT = 0;
815 virtual void resetPrecision() TRTNOEXCEPT = 0;
842 virtual void setOutputType(
int index,
DataType dataType) TRTNOEXCEPT = 0;
853 virtual DataType getOutputType(
int index)
const TRTNOEXCEPT = 0;
863 virtual bool outputTypeIsSet(
int index)
const TRTNOEXCEPT = 0;
872 virtual void resetOutputType(
int index) TRTNOEXCEPT = 0;
1140 TRT_DEPRECATED
virtual void setKernelSize(
DimsHW kernelSize) TRTNOEXCEPT = 0;
1149 TRT_DEPRECATED
virtual DimsHW getKernelSize()
const TRTNOEXCEPT = 0;
1158 virtual void setNbOutputMaps(
int nbOutputMaps) TRTNOEXCEPT = 0;
1165 virtual int getNbOutputMaps()
const TRTNOEXCEPT = 0;
1178 TRT_DEPRECATED
virtual void setStride(
DimsHW stride) TRTNOEXCEPT = 0;
1185 TRT_DEPRECATED
virtual DimsHW getStride()
const TRTNOEXCEPT = 0;
1201 TRT_DEPRECATED
virtual void setPadding(
DimsHW padding) TRTNOEXCEPT = 0;
1210 TRT_DEPRECATED
virtual DimsHW getPadding()
const TRTNOEXCEPT = 0;
1225 virtual void setNbGroups(
int nbGroups) TRTNOEXCEPT = 0;
1232 virtual int getNbGroups()
const TRTNOEXCEPT = 0;
1243 virtual void setKernelWeights(
Weights weights) TRTNOEXCEPT = 0;
1250 virtual Weights getKernelWeights()
const TRTNOEXCEPT = 0;
1262 virtual void setBiasWeights(
Weights weights) TRTNOEXCEPT = 0;
1269 virtual Weights getBiasWeights()
const TRTNOEXCEPT = 0;
1280 TRT_DEPRECATED
virtual void setDilation(
DimsHW dilation) TRTNOEXCEPT = 0;
1289 TRT_DEPRECATED
virtual DimsHW getDilation()
const TRTNOEXCEPT = 0;
1306 virtual void setPrePadding(
Dims padding) TRTNOEXCEPT = 0;
1313 virtual Dims getPrePadding()
const TRTNOEXCEPT = 0;
1326 virtual void setPostPadding(
Dims padding) TRTNOEXCEPT = 0;
1333 virtual Dims getPostPadding()
const TRTNOEXCEPT = 0;
1344 virtual void setPaddingMode(
PaddingMode paddingMode) TRTNOEXCEPT = 0;
1353 virtual PaddingMode getPaddingMode()
const TRTNOEXCEPT = 0;
1362 virtual void setKernelSizeNd(
Dims kernelSize) TRTNOEXCEPT = 0;
1369 virtual Dims getKernelSizeNd()
const TRTNOEXCEPT = 0;
1380 virtual void setStrideNd(
Dims stride) TRTNOEXCEPT = 0;
1387 virtual Dims getStrideNd()
const TRTNOEXCEPT = 0;
1401 virtual void setPaddingNd(
Dims padding) TRTNOEXCEPT = 0;
1410 virtual Dims getPaddingNd()
const TRTNOEXCEPT = 0;
1419 virtual void setDilationNd(
Dims dilation) TRTNOEXCEPT = 0;
1426 virtual Dims getDilationNd()
const TRTNOEXCEPT = 0;
1486 virtual void setNbOutputChannels(
int nbOutputs) TRTNOEXCEPT = 0;
1493 virtual int getNbOutputChannels()
const TRTNOEXCEPT = 0;
1500 virtual void setKernelWeights(
Weights weights) TRTNOEXCEPT = 0;
1507 virtual Weights getKernelWeights()
const TRTNOEXCEPT = 0;
1516 virtual void setBiasWeights(
Weights weights) TRTNOEXCEPT = 0;
1523 virtual Weights getBiasWeights()
const TRTNOEXCEPT = 0;
1574 virtual ActivationType getActivationType()
const TRTNOEXCEPT = 0;
1589 virtual void setAlpha(
float alpha) TRTNOEXCEPT = 0;
1600 virtual void setBeta(
float beta) TRTNOEXCEPT = 0;
1606 virtual float getAlpha()
const TRTNOEXCEPT = 0;
1612 virtual float getBeta()
const TRTNOEXCEPT = 0;
1624 kMAX_AVERAGE_BLEND = 2
1658 virtual PoolingType getPoolingType()
const TRTNOEXCEPT = 0;
1669 TRT_DEPRECATED
virtual void setWindowSize(
DimsHW windowSize) TRTNOEXCEPT = 0;
1678 TRT_DEPRECATED
virtual DimsHW getWindowSize()
const TRTNOEXCEPT = 0;
1691 TRT_DEPRECATED
virtual void setStride(
DimsHW stride) TRTNOEXCEPT = 0;
1700 TRT_DEPRECATED
virtual DimsHW getStride()
const TRTNOEXCEPT = 0;
1713 TRT_DEPRECATED
virtual void setPadding(
DimsHW padding) TRTNOEXCEPT = 0;
1724 TRT_DEPRECATED
virtual DimsHW getPadding()
const TRTNOEXCEPT = 0;
1734 virtual void setBlendFactor(
float blendFactor) TRTNOEXCEPT = 0;
1744 virtual float getBlendFactor()
const TRTNOEXCEPT = 0;
1755 virtual void setAverageCountExcludesPadding(
bool exclusive) TRTNOEXCEPT = 0;
1763 virtual bool getAverageCountExcludesPadding()
const TRTNOEXCEPT = 0;
1780 virtual void setPrePadding(
Dims padding) TRTNOEXCEPT = 0;
1787 virtual Dims getPrePadding()
const TRTNOEXCEPT = 0;
1800 virtual void setPostPadding(
Dims padding) TRTNOEXCEPT = 0;
1807 virtual Dims getPostPadding()
const TRTNOEXCEPT = 0;
1817 virtual void setPaddingMode(
PaddingMode paddingMode) TRTNOEXCEPT = 0;
1825 virtual PaddingMode getPaddingMode()
const TRTNOEXCEPT = 0;
1834 virtual void setWindowSizeNd(
Dims windowSize) TRTNOEXCEPT = 0;
1841 virtual Dims getWindowSizeNd()
const TRTNOEXCEPT = 0;
1852 virtual void setStrideNd(
Dims stride) TRTNOEXCEPT = 0;
1859 virtual Dims getStrideNd()
const TRTNOEXCEPT = 0;
1873 virtual void setPaddingNd(
Dims padding) TRTNOEXCEPT = 0;
1882 virtual Dims getPaddingNd()
const TRTNOEXCEPT = 0;
1903 virtual void setWindowSize(
int windowSize) TRTNOEXCEPT = 0;
1910 virtual int getWindowSize()
const TRTNOEXCEPT = 0;
1918 virtual void setAlpha(
float alpha) TRTNOEXCEPT = 0;
1925 virtual float getAlpha()
const TRTNOEXCEPT = 0;
1933 virtual void setBeta(
float beta) TRTNOEXCEPT = 0;
1940 virtual float getBeta()
const TRTNOEXCEPT = 0;
1948 virtual void setK(
float k) TRTNOEXCEPT = 0;
1955 virtual float getK()
const TRTNOEXCEPT = 0;
2009 virtual void setMode(
ScaleMode mode) TRTNOEXCEPT = 0;
2016 virtual ScaleMode getMode()
const TRTNOEXCEPT = 0;
2023 virtual void setShift(
Weights shift) TRTNOEXCEPT = 0;
2030 virtual Weights getShift()
const TRTNOEXCEPT = 0;
2037 virtual void setScale(
Weights scale) TRTNOEXCEPT = 0;
2044 virtual Weights getScale()
const TRTNOEXCEPT = 0;
2051 virtual void setPower(
Weights power) TRTNOEXCEPT = 0;
2058 virtual Weights getPower()
const TRTNOEXCEPT = 0;
2076 virtual int getChannelAxis()
const TRTNOEXCEPT = 0;
2124 virtual void setAxes(uint32_t axes) TRTNOEXCEPT = 0;
2131 virtual uint32_t getAxes()
const TRTNOEXCEPT = 0;
2159 virtual void setAxis(
int axis) TRTNOEXCEPT = 0;
2166 virtual int getAxis()
const TRTNOEXCEPT = 0;
2190 TRT_DEPRECATED
virtual void setKernelSize(
DimsHW kernelSize) TRTNOEXCEPT = 0;
2199 TRT_DEPRECATED
virtual DimsHW getKernelSize()
const TRTNOEXCEPT = 0;
2208 virtual void setNbOutputMaps(
int nbOutputMaps) TRTNOEXCEPT = 0;
2215 virtual int getNbOutputMaps()
const TRTNOEXCEPT = 0;
2226 TRT_DEPRECATED
virtual void setStride(
DimsHW stride) TRTNOEXCEPT = 0;
2235 TRT_DEPRECATED
virtual DimsHW getStride()
const TRTNOEXCEPT = 0;
2252 TRT_DEPRECATED
virtual void setPadding(
DimsHW padding) TRTNOEXCEPT = 0;
2263 TRT_DEPRECATED
virtual DimsHW getPadding()
const TRTNOEXCEPT = 0;
2278 virtual void setNbGroups(
int nbGroups) TRTNOEXCEPT = 0;
2285 virtual int getNbGroups()
const TRTNOEXCEPT = 0;
2296 virtual void setKernelWeights(
Weights weights) TRTNOEXCEPT = 0;
2303 virtual Weights getKernelWeights()
const TRTNOEXCEPT = 0;
2315 virtual void setBiasWeights(
Weights weights) TRTNOEXCEPT = 0;
2322 virtual Weights getBiasWeights()
const TRTNOEXCEPT = 0;
2339 virtual void setPrePadding(
Dims padding) TRTNOEXCEPT = 0;
2346 virtual Dims getPrePadding()
const TRTNOEXCEPT = 0;
2359 virtual void setPostPadding(
Dims padding) TRTNOEXCEPT = 0;
2366 virtual Dims getPostPadding()
const TRTNOEXCEPT = 0;
2377 virtual void setPaddingMode(
PaddingMode paddingMode) TRTNOEXCEPT = 0;
2386 virtual PaddingMode getPaddingMode()
const TRTNOEXCEPT = 0;
2395 virtual void setKernelSizeNd(
Dims kernelSize) TRTNOEXCEPT = 0;
2402 virtual Dims getKernelSizeNd()
const TRTNOEXCEPT = 0;
2413 virtual void setStrideNd(
Dims stride) TRTNOEXCEPT = 0;
2420 virtual Dims getStrideNd()
const TRTNOEXCEPT = 0;
2434 virtual void setPaddingNd(
Dims padding) TRTNOEXCEPT = 0;
2443 virtual Dims getPaddingNd()
const TRTNOEXCEPT = 0;
2546 virtual void setGatherAxis(
int axis) TRTNOEXCEPT = 0;
2553 virtual int getGatherAxis()
const TRTNOEXCEPT = 0;
2561 virtual void setNbElementWiseDims(
int k) TRTNOEXCEPT = 0;
2568 virtual int getNbElementWiseDims()
const TRTNOEXCEPT = 0;
2734 virtual unsigned getLayerCount()
const TRTNOEXCEPT = 0;
2744 virtual std::size_t getHiddenSize()
const TRTNOEXCEPT = 0;
2754 virtual int getSeqLength()
const TRTNOEXCEPT = 0;
2761 virtual void setOperation(
RNNOperation op) TRTNOEXCEPT = 0;
2768 virtual RNNOperation getOperation()
const TRTNOEXCEPT = 0;
2775 virtual void setInputMode(
RNNInputMode op) TRTNOEXCEPT = 0;
2782 virtual RNNInputMode getInputMode()
const TRTNOEXCEPT = 0;
2795 virtual void setDirection(
RNNDirection op) TRTNOEXCEPT = 0;
2802 virtual RNNDirection getDirection()
const TRTNOEXCEPT = 0;
2918 virtual void setWeights(
Weights weights) TRTNOEXCEPT = 0;
2925 virtual Weights getWeights()
const TRTNOEXCEPT = 0;
2978 virtual void setBias(
Weights bias) TRTNOEXCEPT = 0;
2985 virtual Weights getBias()
const TRTNOEXCEPT = 0;
2993 virtual int getDataLength()
const TRTNOEXCEPT = 0;
3012 virtual void setHiddenState(
ITensor& hidden) TRTNOEXCEPT = 0;
3019 virtual ITensor* getHiddenState()
const TRTNOEXCEPT = 0;
3040 virtual void setCellState(
ITensor& cell) TRTNOEXCEPT = 0;
3047 virtual ITensor* getCellState()
const TRTNOEXCEPT = 0;
3089 virtual int32_t getLayerCount()
const TRTNOEXCEPT = 0;
3090 virtual int32_t getHiddenSize()
const TRTNOEXCEPT = 0;
3091 virtual int32_t getMaxSeqLength()
const TRTNOEXCEPT = 0;
3092 virtual int32_t getDataLength()
const TRTNOEXCEPT = 0;
3108 virtual void setSequenceLengths(
ITensor& seqLengths) TRTNOEXCEPT = 0;
3117 virtual ITensor* getSequenceLengths()
const TRTNOEXCEPT = 0;
3123 virtual void setOperation(
RNNOperation op) TRTNOEXCEPT = 0;
3129 virtual RNNOperation getOperation()
const TRTNOEXCEPT = 0;
3135 virtual void setInputMode(
RNNInputMode op) TRTNOEXCEPT = 0;
3141 virtual RNNInputMode getInputMode()
const TRTNOEXCEPT = 0;
3147 virtual void setDirection(
RNNDirection op) TRTNOEXCEPT = 0;
3153 virtual RNNDirection getDirection()
const TRTNOEXCEPT = 0;
3172 virtual void setWeightsForGate(
int layerIndex,
RNNGateType gate,
bool isW,
Weights weights) TRTNOEXCEPT = 0;
3178 virtual Weights getWeightsForGate(
int layerIndex,
RNNGateType gate,
bool isW)
const TRTNOEXCEPT = 0;
3195 virtual void setBiasForGate(
int layerIndex,
RNNGateType gate,
bool isW,
Weights bias) TRTNOEXCEPT = 0;
3201 virtual Weights getBiasForGate(
int layerIndex,
RNNGateType gate,
bool isW)
const TRTNOEXCEPT = 0;
3215 virtual void setHiddenState(
ITensor& hidden) TRTNOEXCEPT = 0;
3221 virtual ITensor* getHiddenState()
const TRTNOEXCEPT = 0;
3237 virtual void setCellState(
ITensor& cell) TRTNOEXCEPT = 0;
3243 virtual ITensor* getCellState()
const TRTNOEXCEPT = 0;
3298 virtual IPlugin& getPlugin() TRTNOEXCEPT = 0;
3321 virtual IPluginV2& getPlugin() TRTNOEXCEPT = 0;
3442 virtual void setReduceAxes(uint32_t reduceAxes) TRTNOEXCEPT = 0;
3449 virtual uint32_t getReduceAxes()
const TRTNOEXCEPT = 0;
3456 virtual void setKeepDimensions(
bool keepDimensions) TRTNOEXCEPT = 0;
3463 virtual bool getKeepDimensions()
const TRTNOEXCEPT = 0;
3491 TRT_DEPRECATED
virtual void setPrePadding(
DimsHW padding) TRTNOEXCEPT = 0;
3500 TRT_DEPRECATED
virtual DimsHW getPrePadding()
const TRTNOEXCEPT = 0;
3511 TRT_DEPRECATED
virtual void setPostPadding(
DimsHW padding) TRTNOEXCEPT = 0;
3520 TRT_DEPRECATED
virtual DimsHW getPostPadding()
const TRTNOEXCEPT = 0;
3535 virtual void setPrePaddingNd(
Dims padding) TRTNOEXCEPT = 0;
3544 virtual Dims getPrePaddingNd()
const TRTNOEXCEPT = 0;
3555 virtual void setPostPaddingNd(
Dims padding) TRTNOEXCEPT = 0;
3564 virtual Dims getPostPaddingNd()
const TRTNOEXCEPT = 0;
3602 virtual void setFirstTranspose(
Permutation permutation) TRTNOEXCEPT = 0;
3611 virtual Permutation getFirstTranspose()
const TRTNOEXCEPT = 0;
3633 virtual void setReshapeDimensions(
Dims dimensions) TRTNOEXCEPT = 0;
3643 virtual Dims getReshapeDimensions()
const TRTNOEXCEPT = 0;
3679 virtual void setSecondTranspose(
Permutation permutation) TRTNOEXCEPT = 0;
3688 virtual Permutation getSecondTranspose()
const TRTNOEXCEPT = 0;
3751 virtual void setStart(
Dims start) TRTNOEXCEPT = 0;
3763 virtual Dims getStart()
const TRTNOEXCEPT = 0;
3774 virtual void setSize(
Dims size) TRTNOEXCEPT = 0;
3786 virtual Dims getSize()
const TRTNOEXCEPT = 0;
3797 virtual void setStride(
Dims stride) TRTNOEXCEPT = 0;
3809 virtual Dims getStride()
const TRTNOEXCEPT = 0;
3816 virtual void setMode(
SliceMode mode) TRTNOEXCEPT = 0;
3823 virtual SliceMode getMode()
const TRTNOEXCEPT = 0;
3900 virtual void setOperation(
TopKOperation op) TRTNOEXCEPT = 0;
3916 virtual void setK(
int k) TRTNOEXCEPT = 0;
3923 virtual int getK()
const TRTNOEXCEPT = 0;
3930 virtual void setReduceAxes(uint32_t reduceAxes) TRTNOEXCEPT = 0;
3937 virtual uint32_t getReduceAxes()
const TRTNOEXCEPT = 0;
4011 virtual void setOperation(
int index,
MatrixOperation op) TRTNOEXCEPT = 0;
4018 virtual MatrixOperation getOperation(
int index)
const TRTNOEXCEPT = 0;
4028 TRT_DEPRECATED
virtual void setTranspose(
int index,
bool val) TRTNOEXCEPT = 0;
4037 TRT_DEPRECATED
virtual bool getTranspose(
int index)
const TRTNOEXCEPT = 0;
4095 virtual void setWeights(
Weights weights) TRTNOEXCEPT = 0;
4102 virtual Weights getWeights()
const TRTNOEXCEPT = 0;
4111 virtual void setDimensions(
Dims dimensions) TRTNOEXCEPT = 0;
4120 virtual Dims getDimensions()
const TRTNOEXCEPT = 0;
4194 virtual void setOutputDimensions(
Dims dimensions) TRTNOEXCEPT = 0;
4201 virtual Dims getOutputDimensions()
const TRTNOEXCEPT = 0;
4221 virtual void setScales(
const float* scales,
int nbScales) TRTNOEXCEPT = 0;
4237 virtual int getScales(
int size,
float* scales)
const TRTNOEXCEPT = 0;
4246 virtual void setResizeMode(
ResizeMode resizeMode) TRTNOEXCEPT = 0;
4253 virtual ResizeMode getResizeMode()
const TRTNOEXCEPT = 0;
4264 virtual void setAlignCorners(
bool alignCorners) TRTNOEXCEPT = 0;
4271 virtual bool getAlignCorners()
const TRTNOEXCEPT = 0;
4340 virtual ILoop* getLoop()
const noexcept = 0;
4387 virtual LoopOutput getLoopOutput()
const noexcept = 0;
4401 virtual void setAxis(
int axis) noexcept = 0;
4404 virtual int getAxis()
const noexcept = 0;
4432 virtual TripLimit getTripLimit()
const noexcept = 0;
4439 virtual void setAxis(
int axis) noexcept = 0;
4442 virtual int getAxis()
const noexcept = 0;
4449 virtual void setReverse(
bool reverse) noexcept = 0;
4452 virtual bool getReverse()
const noexcept = 0;
4496 virtual IIteratorLayer* addIterator(
ITensor& tensor,
int axis = 0,
bool reverse =
false) noexcept = 0;
4515 virtual void setName(
const char* name) noexcept = 0;
4522 virtual const char* getName()
const noexcept = 0;
4586 virtual void setDimensions(
Dims dimensions) noexcept = 0;
4598 virtual Dims getDimensions()
const noexcept = 0;
4627 virtual void setAlpha(
double alpha) noexcept = 0;
4639 virtual double getAlpha()
const noexcept = 0;
4654 virtual void setBeta(
double beta) noexcept = 0;
4666 virtual double getBeta()
const noexcept = 0;
4761 virtual void markOutput(
ITensor& tensor) TRTNOEXCEPT = 0;
4849 virtual ILRNLayer* addLRN(
ITensor& input,
int window,
float alpha,
float beta,
float k) TRTNOEXCEPT = 0;
4997 TRT_DEPRECATED
virtual IRNNLayer* addRNN(
ITensor& inputs,
int layerCount, std::size_t hiddenSize,
int maxSeqLen,
5017 ITensor*
const* inputs,
int nbInputs,
IPlugin& plugin) TRTNOEXCEPT = 0;
5098 TRT_DEPRECATED
virtual void setConvolutionOutputDimensionsFormula(
5128 TRT_DEPRECATED
virtual void setDeconvolutionOutputDimensionsFormula(
5151 virtual int getNbLayers()
const TRTNOEXCEPT = 0;
5162 virtual ILayer* getLayer(
int index)
const TRTNOEXCEPT = 0;
5171 virtual int getNbInputs()
const TRTNOEXCEPT = 0;
5182 virtual ITensor* getInput(
int index)
const TRTNOEXCEPT = 0;
5193 virtual int getNbOutputs()
const TRTNOEXCEPT = 0;
5204 virtual ITensor* getOutput(
int index)
const TRTNOEXCEPT = 0;
5209 virtual void destroy() TRTNOEXCEPT = 0;
5332 ITensor& input0,
bool transpose0,
ITensor& input1,
bool transpose1) TRTNOEXCEPT = 0;
5418 ITensor& input, int32_t layerCount, int32_t hiddenSize, int32_t maxSeqLen,
RNNOperation op) TRTNOEXCEPT = 0;
5462 virtual void removeTensor(
ITensor& tensor) TRTNOEXCEPT = 0;
5471 virtual void unmarkOutput(
ITensor& tensor) TRTNOEXCEPT = 0;
5522 virtual void setName(
const char* name) TRTNOEXCEPT = 0;
5533 virtual const char* getName()
const TRTNOEXCEPT = 0;
5564 virtual bool hasImplicitBatchDimension()
const TRTNOEXCEPT = 0;
5579 virtual bool markOutputForShapes(
ITensor& tensor) TRTNOEXCEPT = 0;
5588 virtual bool unmarkOutputForShapes(
ITensor& tensor) TRTNOEXCEPT = 0;
5706 virtual bool hasExplicitPrecision()
const TRTNOEXCEPT = 0;
5717 virtual ILoop* addLoop() noexcept = 0;
5763 kLEGACY_CALIBRATION = 0,
5764 kENTROPY_CALIBRATION = 1,
5765 kENTROPY_CALIBRATION_2 = 2,
5766 kMINMAX_CALIBRATION = 3,
5794 virtual int getBatchSize()
const TRTNOEXCEPT = 0;
5809 virtual bool getBatch(
void* bindings[],
const char* names[],
int nbBindings) TRTNOEXCEPT = 0;
5825 virtual const void* readCalibrationCache(std::size_t& length) TRTNOEXCEPT = 0;
5835 virtual void writeCalibrationCache(
const void* ptr, std::size_t length) TRTNOEXCEPT = 0;
5909 virtual double getQuantile()
const TRTNOEXCEPT = 0;
5917 virtual double getRegressionCutoff()
const TRTNOEXCEPT = 0;
5931 virtual const void* readHistogramCache(std::size_t& length) TRTNOEXCEPT = 0;
5941 virtual void writeHistogramCache(
const void* ptr, std::size_t length) TRTNOEXCEPT = 0;
5995 virtual void setMinTimingIterations(
int minTiming) TRTNOEXCEPT = 0;
6004 virtual int getMinTimingIterations()
const TRTNOEXCEPT = 0;
6014 virtual void setAvgTimingIterations(
int avgTiming) TRTNOEXCEPT = 0;
6023 virtual int getAvgTimingIterations()
const TRTNOEXCEPT = 0;
6033 virtual void setEngineCapability(
EngineCapability capability) TRTNOEXCEPT = 0;
6049 virtual void setInt8Calibrator(
IInt8Calibrator* calibrator) TRTNOEXCEPT = 0;
6063 virtual void setMaxWorkspaceSize(std::size_t workspaceSize) TRTNOEXCEPT = 0;
6074 virtual std::size_t getMaxWorkspaceSize()
const TRTNOEXCEPT = 0;
6088 virtual void setFlags(BuilderFlags builderFlags) TRTNOEXCEPT = 0;
6097 virtual BuilderFlags getFlags()
const TRTNOEXCEPT = 0;
6106 virtual void clearFlag(
BuilderFlag builderFlag) TRTNOEXCEPT = 0;
6115 virtual void setFlag(
BuilderFlag builderFlag) TRTNOEXCEPT = 0;
6126 virtual bool getFlag(
BuilderFlag builderFlag)
const TRTNOEXCEPT = 0;
6139 virtual void setDeviceType(
const ILayer* layer,
DeviceType deviceType) TRTNOEXCEPT = 0;
6145 virtual DeviceType getDeviceType(
const ILayer* layer)
const TRTNOEXCEPT = 0;
6152 virtual bool isDeviceTypeSet(
const ILayer* layer)
const TRTNOEXCEPT = 0;
6159 virtual void resetDeviceType(
const ILayer* layer) TRTNOEXCEPT = 0;
6165 virtual bool canRunOnDLA(
const ILayer* layer)
const TRTNOEXCEPT = 0;
6175 virtual void setDLACore(
int dlaCore) TRTNOEXCEPT = 0;
6181 virtual int getDLACore()
const TRTNOEXCEPT = 0;
6188 virtual void setDefaultDeviceType(
DeviceType deviceType) TRTNOEXCEPT = 0;
6195 virtual DeviceType getDefaultDeviceType()
const TRTNOEXCEPT = 0;
6202 virtual void reset() TRTNOEXCEPT = 0;
6209 virtual void destroy() TRTNOEXCEPT = 0;
6218 virtual void setProfileStream(
const cudaStream_t stream) TRTNOEXCEPT = 0;
6227 virtual cudaStream_t getProfileStream()
const TRTNOEXCEPT = 0;
6248 virtual int getNbOptimizationProfiles()
const noexcept = 0;
6299 constexpr
inline int EnumMax<NetworkDefinitionCreationFlag>()
6336 virtual void setMaxBatchSize(
int batchSize) TRTNOEXCEPT = 0;
6346 virtual int getMaxBatchSize()
const TRTNOEXCEPT = 0;
6357 TRT_DEPRECATED
virtual void setMaxWorkspaceSize(std::size_t workspaceSize) TRTNOEXCEPT = 0;
6368 TRT_DEPRECATED
virtual std::size_t getMaxWorkspaceSize()
const TRTNOEXCEPT = 0;
6382 TRT_DEPRECATED
virtual void setHalf2Mode(
bool mode) TRTNOEXCEPT = 0;
6391 TRT_DEPRECATED
virtual bool getHalf2Mode()
const TRTNOEXCEPT = 0;
6401 TRT_DEPRECATED
virtual void setDebugSync(
bool sync) TRTNOEXCEPT = 0;
6410 TRT_DEPRECATED
virtual bool getDebugSync()
const TRTNOEXCEPT = 0;
6422 TRT_DEPRECATED
virtual void setMinFindIterations(
int minFind) TRTNOEXCEPT = 0;
6431 TRT_DEPRECATED
virtual int getMinFindIterations()
const TRTNOEXCEPT = 0;
6443 TRT_DEPRECATED
virtual void setAverageFindIterations(
int avgFind) TRTNOEXCEPT = 0;
6452 TRT_DEPRECATED
virtual int getAverageFindIterations()
const TRTNOEXCEPT = 0;
6467 virtual bool platformHasFastFp16()
const TRTNOEXCEPT = 0;
6472 virtual bool platformHasFastInt8()
const TRTNOEXCEPT = 0;
6477 virtual void destroy() TRTNOEXCEPT = 0;
6490 TRT_DEPRECATED
virtual void setInt8Mode(
bool mode) TRTNOEXCEPT = 0;
6499 TRT_DEPRECATED
virtual bool getInt8Mode()
const TRTNOEXCEPT = 0;
6506 TRT_DEPRECATED
virtual void setInt8Calibrator(
IInt8Calibrator* calibrator) TRTNOEXCEPT = 0;
6520 TRT_DEPRECATED
virtual void setDeviceType(
ILayer* layer,
DeviceType deviceType) TRTNOEXCEPT = 0;
6528 TRT_DEPRECATED
virtual DeviceType getDeviceType(
const ILayer* layer)
const TRTNOEXCEPT = 0;
6537 TRT_DEPRECATED
virtual bool isDeviceTypeSet(
const ILayer* layer)
const TRTNOEXCEPT = 0;
6546 TRT_DEPRECATED
virtual void resetDeviceType(
ILayer* layer) TRTNOEXCEPT = 0;
6552 TRT_DEPRECATED
virtual bool canRunOnDLA(
const ILayer* layer)
const TRTNOEXCEPT = 0;
6561 TRT_DEPRECATED
virtual void setDefaultDeviceType(
DeviceType deviceType) TRTNOEXCEPT = 0;
6568 TRT_DEPRECATED
virtual DeviceType getDefaultDeviceType()
const TRTNOEXCEPT = 0;
6577 virtual int getMaxDLABatchSize()
const TRTNOEXCEPT = 0;
6588 TRT_DEPRECATED
virtual void allowGPUFallback(
bool setFallBackMode) TRTNOEXCEPT = 0;
6593 virtual int getNbDLACores()
const TRTNOEXCEPT = 0;
6605 TRT_DEPRECATED
virtual void setDLACore(
int dlaCore) TRTNOEXCEPT = 0;
6613 TRT_DEPRECATED
virtual int getDLACore()
const TRTNOEXCEPT = 0;
6639 virtual void setGpuAllocator(
IGpuAllocator* allocator) TRTNOEXCEPT = 0;
6652 TRT_DEPRECATED
virtual void setFp16Mode(
bool mode) TRTNOEXCEPT = 0;
6661 TRT_DEPRECATED
virtual bool getFp16Mode()
const TRTNOEXCEPT = 0;
6681 TRT_DEPRECATED
virtual void setStrictTypeConstraints(
bool mode) TRTNOEXCEPT = 0;
6690 TRT_DEPRECATED
virtual bool getStrictTypeConstraints()
const TRTNOEXCEPT = 0;
6697 TRT_DEPRECATED
virtual void setRefittable(
bool canRefit) TRTNOEXCEPT = 0;
6706 TRT_DEPRECATED
virtual bool getRefittable()
const TRTNOEXCEPT = 0;
6713 TRT_DEPRECATED
virtual void setEngineCapability(
EngineCapability capability) TRTNOEXCEPT = 0;
6722 TRT_DEPRECATED
virtual EngineCapability getEngineCapability()
const TRTNOEXCEPT = 0;
6778 virtual void setErrorRecorder(
IErrorRecorder* recorder) TRTNOEXCEPT = 0;
6790 virtual IErrorRecorder* getErrorRecorder()
const TRTNOEXCEPT = 0;
6795 virtual void reset() TRTNOEXCEPT = 0;
6804 extern "C" TENSORRTAPI
void* createInferBuilder_INTERNAL(
void* logger,
int version);
6819 return static_cast<IBuilder*
>(createInferBuilder_INTERNAL(&logger, NV_TENSORRT_VERSION));
int w() const
Get the width.
Definition: NvInfer.h:400
int n() const
Get the index count.
Definition: NvInfer.h:358
Use SAME padding, with prePadding <= postPadding.
An engine for executing inference on a built network, with functionally unsafe features.
Definition: NvInferRuntime.h:1115
Substract the second element from the first.
Perform the normal matrix multiplication in the first recurrent layer.
DataType
The type of weights and tensors.
Definition: NvInferRuntimeCommon.h:162
PaddingMode
Enumerates the modes of padding to perform in convolution, deconvolution and pooling layer...
Definition: NvInfer.h:1100
NetworkDefinitionCreationFlag
List of immutable network properties expressed at network creation time. NetworkDefinitionCreationFla...
Definition: NvInfer.h:6276
DimsNCHW(int batchSize, int channels, int height, int width)
Construct a DimsNCHW given batch size, channel count, height and width.
Definition: NvInfer.h:338
constexpr int EnumMax< CalibrationAlgoType >()
Maximum number of elements in CalibrationAlgoType enum.
Definition: NvInfer.h:5770
RNNOperation
Enumerates the RNN operations that may be performed by an RNN layer.
Definition: NvInfer.h:2653
Logical XOR of two elements.
Check if element in first tensor is less than corresponding element in second tensor.
A Softmax layer in a network definition.
Definition: NvInfer.h:2090
constexpr int EnumMax< TripLimit >()
Maximum number of elements in TripLimit enum.
Definition: NvInfer.h:4329
Check if two elements are equal.
MatrixOperation
Enumerates the operations that may be performed on a tensor by IMatrixMultiplyLayer before multiplica...
Definition: NvInfer.h:3949
Definition: NvInfer.h:3567
Plugin class for user-implemented layers.
Definition: NvInferRuntimeCommon.h:344
constexpr int EnumMax< RNNDirection >()
Maximum number of elements in RNNDirection enum.
Definition: NvInfer.h:2681
Single gate RNN w/ TANH activation function.
Layer that represents an unary operation.
Definition: NvInfer.h:3372
Check if element in first tensor is greater than corresponding element in second tensor.
struct CUstream_st * cudaStream_t
Forward declaration of cudaStream_t.
Definition: NvInferRuntimeCommon.h:112
An Activation layer in a network definition.
Definition: NvInfer.h:1559
IBuilder * createInferBuilder(ILogger &logger)
Create an instance of an IBuilder class.
Definition: NvInfer.h:6817
BuilderFlag
Definition: NvInfer.h:5961
constexpr int EnumMax< PaddingMode >()
Maximum number of elements in PaddingMode enum.
Definition: NvInfer.h:1111
int w() const
Get the width.
Definition: NvInfer.h:273
RNNDirection
Enumerates the RNN direction that may be performed by an RNN layer.
Definition: NvInfer.h:2674
Layer that represents a Matrix Multiplication.
Definition: NvInfer.h:4002
DimsCHW()
Construct an empty DimsCHW object.
Definition: NvInfer.h:212
No operation is performed on the first recurrent layer.
int c() const
Get the channel count.
Definition: NvInfer.h:372
Holds properties for configuring a builder to produce an engine.
Definition: NvInfer.h:5982
CalibrationAlgoType getAlgorithm() override
Definition: NvInfer.h:5872
constexpr int EnumMax< RNNOperation >()
Maximum number of elements in RNNOperation enum.
Definition: NvInfer.h:2662
int h() const
Get the height.
Definition: NvInfer.h:386
A convolution layer in a network definition.
Definition: NvInfer.h:1128
Definition: NvInfer.h:4336
A RaggedSoftmax layer in a network definition.
Definition: NvInfer.h:4057
ScaleMode
Controls how shift, scale and power are applied in a Scale layer.
Definition: NvInfer.h:1966
Coordinates wrap around periodically.
Plugin class for user-implemented layers.
Definition: NvInferRuntime.h:134
Layer that represents a constant value.
Definition: NvInfer.h:4083
Logical AND of two elements.
A Scale layer in a network definition.
Definition: NvInfer.h:2001
Layer type for getting shape of a tensor.
Definition: NvInfer.h:3862
Enable FP16 layer selection, with FP32 fallback.
Use SAME padding, with prePadding >= postPadding.
Definition: NvInfer.h:4458
static const int MAX_DIMS
The maximum number of dimensions supported for a tensor.
Definition: NvInferRuntimeCommon.h:209
A fully connected layer in a network definition. This layer expects an input tensor of three or more ...
Definition: NvInfer.h:1476
Use CAFFE padding, rounding output size down, uses prePadding value.
Layer that represents a parametric ReLU operation.
Definition: NvInfer.h:4133
int w() const
Get the width.
Definition: NvInfer.h:165
ReduceOperation
Enumerates the reduce operations that may be performed by a Reduce layer.
Definition: NvInfer.h:3398
A LRN layer in a network definition.
Definition: NvInfer.h:1894
Descriptor for three-dimensional data.
Definition: NvInfer.h:172
Fail with error when the coordinates are out of bounds. This is the default.
constexpr int EnumMax< ElementWiseOperation >()
Maximum number of elements in ElementWiseOperation enum.
Definition: NvInfer.h:2491
uint32_t BuilderFlags
It is capable of representing one or more BuilderFlags by binary OR operations, e.g., 1U << BuilderFlag::kFP16 | 1U << BuilderFlag::kDEBUG.
Definition: NvInfer.h:5952
TensorLocation
The location for tensor data storage, device or host.
Definition: NvInferRuntimeCommon.h:926
Definition: NvInfer.h:2537
Builds an engine from a network definition.
Definition: NvInfer.h:6312
Generate evenly spaced numbers over a specified interval.
Layer that represents a TopK reduction.
Definition: NvInfer.h:3892
An RNN layer in a network definition, version 2.
Definition: NvInfer.h:3086
int & h()
Get the height.
Definition: NvInfer.h:252
Per-channel coefficients.
Elements correspond to different spatial data.
The TensorRT API version 1 namespace.
constexpr int EnumMax< LayerType >()
Maximum number of elements in LayerType enum.
Definition: NvInfer.h:449
CalibrationAlgoType getAlgorithm() override
Definition: NvInfer.h:5887
int & n()
Get the index count.
Definition: NvInfer.h:351
int c() const
Get the channel count.
Definition: NvInfer.h:245
int & w()
Get the width.
Definition: NvInfer.h:266
Layer that represents a reduction operator across Shape, Int32, Float, and Half tensors.
Definition: NvInfer.h:3420
Definition: NvInfer.h:5895
PoolingType
The type of pooling to perform in a pooling layer.
Definition: NvInfer.h:1620
int h() const
Get the height.
Definition: NvInfer.h:259
Generate an output tensor with specified mode.
Definition: NvInfer.h:4574
SliceMode
Controls how ISliceLayer handles out of bounds coordinates.
Definition: NvInfer.h:3699
Inverse hyperbolic tangent.
int & w()
Get the width.
Definition: NvInfer.h:158
CalibrationAlgoType getAlgorithm() override
Definition: NvInfer.h:5901
constexpr int EnumMax< FillOperation >()
Maximum number of elements in FillOperation enum.
Definition: NvInfer.h:4551
Descriptor for data with one channel dimension and two spatial dimensions.
Definition: NvInfer.h:206
The first element to the power of the second element.
A network definition for input to the builder.
Definition: NvInfer.h:4717
Like kNONE, but transpose the matrix dimensions.
Output value is concatenation of values of tensor for each iteration, in forward order.
Definition: NvInfer.h:4343
Divide the first element by the second.
Layer type for pluginV2.
Definition: NvInfer.h:3313
Product of the two elements.
Dims2()
Construct an empty Dims2 object.
Definition: NvInfer.h:91
TopKOperation
Enumerates the operations that may be performed by a TopK layer.
Definition: NvInfer.h:3873
Dims3(int d0, int d1, int d2)
Construct a Dims3 from 3 elements.
Definition: NvInfer.h:191
Descriptor for four-dimensional data.
Definition: NvInfer.h:280
ActivationType
Forward declare IGpuAllocator for use in other interfaces.
Definition: NvInferRuntimeCommon.h:133
Descriptor for data with one index dimension, one channel dimension and two spatial dimensions...
Definition: NvInfer.h:316
TRT_DEPRECATED DimensionType type[MAX_DIMS]
The type of each dimension.
Definition: NvInferRuntimeCommon.h:212
Optimization profile for dynamic input dimensions and shape tensors.
Definition: NvInferRuntime.h:997
Inverse hyperbolic cosine.
A resize layer in a network definition.
Definition: NvInfer.h:4176
constexpr int EnumMax< BuilderFlag >()
Maximum number of builder flags in BuilderFlag enum.
Definition: NvInfer.h:5972
DimsHW()
Construct an empty DimsHW object.
Definition: NvInfer.h:121
Use explicit padding, rounding output size up.
Base class for all layer classes in a network definition.
Definition: NvInfer.h:704
Reference counted application-implemented error reporting interface for TensorRT objects.
Definition: NvInferRuntimeCommon.h:1142
Dims4(int d0, int d1, int d2, int d3)
Construct a Dims4 from 4 elements.
Definition: NvInfer.h:300
Slices an input tensor into an output tensor based on the offset and strides.
Definition: NvInfer.h:3739
int & h()
Get the height.
Definition: NvInfer.h:379
int & h()
Get the height.
Definition: NvInfer.h:144
Mark the network to be an explicit batch network.
Enables strict type constraints.
int & c()
Get the channel count.
Definition: NvInfer.h:365
Structure to define the dimensions of a tensor.
Definition: NvInferRuntimeCommon.h:206
Network iterates from first to last and vice versa and outputs concatenated.
Layer type for shuffling data.
Definition: NvInfer.h:3590
DimsCHW(int channels, int height, int width)
Construct a DimsCHW given channel count, height and width.
Definition: NvInfer.h:226
Definition: NvInfer.h:5866
LoopOutput
Enum that describes kinds of loop outputs.
Definition: NvInfer.h:4300
A elementwise layer in a network definition.
Definition: NvInfer.h:2507
A Pooling layer in a network definition.
Definition: NvInfer.h:1641
constexpr int EnumMax< UnaryOperation >()
Maximum number of elements in UnaryOperation enum.
Definition: NvInfer.h:3360
int d[MAX_DIMS]
The extent of each dimension.
Definition: NvInferRuntimeCommon.h:211
Minimum of the two elements.
constexpr int EnumMax< LoopOutput >()
Maximum number of elements in LoopOutput enum.
Definition: NvInfer.h:4313
constexpr int EnumMax< SliceMode >()
Maximum number of elements in SliceMode enum.
Definition: NvInfer.h:3706
ElementWiseOperation
Enumerates the binary operations that may be performed by an ElementWise layer.
Definition: NvInfer.h:2472
Three-gate network consisting of Gated Recurrent Units.
RNNGateType
Identifies an individual gate within an RNN cell.
Definition: NvInfer.h:3060
Network iterations from first input to last input.
Output value is value of tensor for last iteration.
int & c()
Get the channel count.
Definition: NvInfer.h:238
Single gate RNN w/ ReLU activation function.
Dims3()
Construct an empty Dims3 object.
Definition: NvInfer.h:178
uint32_t TensorFormats
It is capable of representing one or more TensorFormat by binary OR operations, e.g., 1U << TensorFormats::kCHW4 | 1U << TensorFormats::kCHW32.
Definition: NvInferRuntimeCommon.h:221
A tensor in a network definition.
Definition: NvInfer.h:463
Logical OR of two elements.
An array of weights used as a layer parameter.
Definition: NvInferRuntime.h:98
int & w()
Get the width.
Definition: NvInfer.h:393
int h() const
Get the height.
Definition: NvInfer.h:151
Enable Int8 layer selection, with FP32 fallback with FP16 fallback if kFP16 also specified.
Mark the network to be an explicit precision network.
Dims2(int d0, int d1)
Construct a Dims2 from 2 elements.
Definition: NvInfer.h:103
Enable building a refittable engine.
Dims4()
Construct an empty Dims2 object.
Definition: NvInfer.h:286
int nbDims
The number of dimensions.
Definition: NvInferRuntimeCommon.h:210
Application-implemented interface for calibration.
Definition: NvInfer.h:5786
Generate a tensor with random values drawn from a uniform distribution.
Application-implemented logging interface for the builder, engine and runtime.
Definition: NvInferRuntimeCommon.h:986
DimsHW(int height, int width)
Construct a DimsHW given height and width.
Definition: NvInfer.h:133
constexpr int EnumMax< ReduceOperation >()
Maximum number of elements in ReduceOperation enum.
Definition: NvInfer.h:3408
Identical coefficients across all elements of the tensor.
Plugin class for user-implemented layers.
Definition: NvInferRuntime.h:238
Layer that represents a padding operation.
Definition: NvInfer.h:3479
Floor division of the first element by the second.
Definition: NvInfer.h:5881
constexpr int EnumMax< RNNGateType >()
Maximum number of elements in RNNGateType enum.
Definition: NvInfer.h:3072
constexpr int EnumMax< RNNInputMode >()
Maximum number of elements in RNNInputMode enum.
Definition: NvInfer.h:2708
Enable debugging of layers via synchronizing after every layer.
CalibrationAlgoType
Version of calibration algorithm to use.
Definition: NvInfer.h:5761
EngineCapability
Forward declaration of IPluginFactory for use by other interfaces.
Definition: NvInferRuntime.h:76
Enable layers marked to execute on GPU if layer cannot execute on DLA.
Use explicit padding, rounding output size down.
DimsNCHW()
Construct an empty DimsNCHW object.
Definition: NvInfer.h:322
LayerType
The type values of layer classes.
Definition: NvInfer.h:410
A layer that represents the identity function.
Definition: NvInfer.h:4071
Definition: NvInfer.h:4429
RNNInputMode
Enumerates the RNN input modes that may occur with an RNN layer.
Definition: NvInfer.h:2701
A RNN layer in a network definition.
Definition: NvInfer.h:2726
Definition: NvInfer.h:4435
Layer type for plugins.
Definition: NvInfer.h:3290
FillOperation
Enumerates the tensor fill operations that may performed by a fill layer.
Definition: NvInfer.h:4544
uint32_t NetworkDefinitionCreationFlags
This bitset is capable of representing one or more NetworkDefinitionCreationFlag flags constructed wi...
Definition: NvInfer.h:6265
Four-gate LSTM network w/o peephole connections.
constexpr int EnumMax< MatrixOperation >()
Maximum number of elements in MatrixOperation enum.
Definition: NvInfer.h:3972
Output value is concatenation of values of tensor for each iteration, in reverse order.
TripLimit
Enum that describes kinds of trip limits.
Definition: NvInfer.h:4319
#define _TENSORRT_OVERRIDE
Items that are marked as deprecated will be removed in a future release.
Definition: NvInferRuntimeCommon.h:62
Application-implemented class for controlling allocation on the GPU.
Definition: NvInferRuntimeCommon.h:943
constexpr int EnumMax< TopKOperation >()
Maximum number of elements in TopKOperation enum.
Definition: NvInfer.h:3880
constexpr int EnumMax< PoolingType >()
Maximum number of elements in PoolingType enum.
Definition: NvInfer.h:1628
constexpr int EnumMax< ScaleMode >()
Maximum number of elements in ScaleMode enum.
Definition: NvInfer.h:1974
Descriptor for two-dimensional spatial data.
Definition: NvInfer.h:115
UnaryOperation
Enumerates the unary operations that may be performed by a Unary layer.
Definition: NvInfer.h:3334
Definition: NvInfer.h:4531
constexpr int EnumMax< ResizeMode >()
Maximum number of elements in ResizeMode enum.
Definition: NvInfer.h:4151
DeviceType
The device that this layer/network will execute on.
Definition: NvInferRuntime.h:675
Elements correspond to different batch index.
Descriptor for two-dimensional data.
Definition: NvInfer.h:85
A concatenation layer in a network definition.
Definition: NvInfer.h:2145
ResizeMode
Enumerates various modes of resize in the resize layer. Resize mode set using setResizeMode().
Definition: NvInfer.h:4144
CalibrationAlgoType getAlgorithm() override
Definition: NvInfer.h:5857
A deconvolution layer in a network definition.
Definition: NvInfer.h:2178
Definition: NvInfer.h:4384
Use CAFFE padding, rounding output size up, uses prePadding value.
Definition: NvInfer.h:5851