160 static constexpr int32_t kVALUE = 14;
199 mImpl->setName(name);
211 return mImpl->getName();
230 mImpl->setDimensions(dimensions);
244 return mImpl->getDimensions();
259 mImpl->setType(type);
271 return mImpl->getType();
288 return mImpl->setDynamicRange(min, max);
296 return mImpl->isNetworkInput();
304 return mImpl->isNetworkOutput();
321 mImpl->setBroadcastAcrossBatch(broadcastAcrossBatch);
335 return mImpl->getBroadcastAcrossBatch();
347 return mImpl->getLocation();
366 mImpl->setLocation(location);
378 return mImpl->dynamicRangeIsSet();
386 mImpl->resetDynamicRange();
396 return mImpl->getDynamicRangeMin();
406 return mImpl->getDynamicRangeMax();
428 mImpl->setAllowedFormats(formats);
441 return mImpl->getAllowedFormats();
472 return mImpl->isShapeTensor();
493 return mImpl->isExecutionTensor();
519 mImpl->setDimensionName(index, name);
534 return mImpl->getDimensionName(index);
559 return mLayer->getType();
573 mLayer->setName(name);
583 return mLayer->getName();
591 return mLayer->getNbInputs();
604 return mLayer->getInput(index);
612 return mLayer->getNbOutputs();
622 return mLayer->getOutput(index);
639 return mLayer->setInput(index, tensor);
670 mLayer->setPrecision(dataType);
682 return mLayer->getPrecision();
694 return mLayer->precisionIsSet();
704 mLayer->resetPrecision();
751 mLayer->setOutputType(index, dataType);
766 return mLayer->getOutputType(index);
780 return mLayer->outputTypeIsSet(index);
792 return mLayer->resetOutputType(index);
810 mLayer->setMetadata(metadata);
823 return mLayer->getMetadata();
828 apiv::VLayer* mLayer;
1005 static constexpr int32_t kVALUE = 4;
1033 mImpl->setNbOutputMaps(nbOutputMaps);
1043 return mImpl->getNbOutputMaps();
1063 mImpl->setNbGroups(nbGroups);
1073 return mImpl->getNbGroups();
1087 mImpl->setKernelWeights(weights);
1097 return mImpl->getKernelWeights();
1112 mImpl->setBiasWeights(weights);
1122 return mImpl->getBiasWeights();
1139 mImpl->setPrePadding(padding);
1149 return mImpl->getPrePadding();
1166 mImpl->setPostPadding(padding);
1176 return mImpl->getPostPadding();
1190 mImpl->setPaddingMode(paddingMode);
1202 return mImpl->getPaddingMode();
1215 mImpl->setKernelSizeNd(kernelSize);
1225 return mImpl->getKernelSizeNd();
1240 mImpl->setStrideNd(stride);
1250 return mImpl->getStrideNd();
1268 mImpl->setPaddingNd(padding);
1280 return mImpl->getPaddingNd();
1294 mImpl->setDilationNd(dilation);
1304 return mImpl->getDilationNd();
1353 mImpl->setActivationType(type);
1363 return mImpl->getActivationType();
1378 mImpl->setAlpha(alpha);
1392 mImpl->setBeta(beta);
1401 return mImpl->getAlpha();
1410 return mImpl->getBeta();
1440 static constexpr int32_t kVALUE = 3;
1467 mImpl->setPoolingType(type);
1477 return mImpl->getPoolingType();
1492 mImpl->setBlendFactor(blendFactor);
1505 return mImpl->getBlendFactor();
1519 mImpl->setAverageCountExcludesPadding(exclusive);
1530 return mImpl->getAverageCountExcludesPadding();
1548 mImpl->setPrePadding(padding);
1558 return mImpl->getPrePadding();
1576 mImpl->setPostPadding(padding);
1586 return mImpl->getPostPadding();
1599 mImpl->setPaddingMode(paddingMode);
1610 return mImpl->getPaddingMode();
1623 mImpl->setWindowSizeNd(windowSize);
1633 return mImpl->getWindowSizeNd();
1648 mImpl->setStrideNd(stride);
1658 return mImpl->getStrideNd();
1677 mImpl->setPaddingNd(padding);
1689 return mImpl->getPaddingNd();
1720 mImpl->setWindowSize(windowSize);
1730 return mImpl->getWindowSize();
1742 mImpl->setAlpha(alpha);
1752 return mImpl->getAlpha();
1764 mImpl->setBeta(beta);
1774 return mImpl->getBeta();
1796 return mImpl->getK();
1862 mImpl->setMode(mode);
1872 return mImpl->getMode();
1882 mImpl->setShift(shift);
1892 return mImpl->getShift();
1902 mImpl->setScale(scale);
1912 return mImpl->getScale();
1922 mImpl->setPower(power);
1932 return mImpl->getPower();
1947 return mImpl->getChannelAxis();
1968 mImpl->setChannelAxis(channelAxis);
2021 mImpl->setAxes(axes);
2031 return mImpl->getAxes();
2067 mImpl->setAxis(axis);
2077 return mImpl->getAxis();
2104 mImpl->setNbOutputMaps(nbOutputMaps);
2114 return mImpl->getNbOutputMaps();
2134 mImpl->setNbGroups(nbGroups);
2144 return mImpl->getNbGroups();
2158 mImpl->setKernelWeights(weights);
2168 return mImpl->getKernelWeights();
2183 mImpl->setBiasWeights(weights);
2193 return mImpl->getBiasWeights();
2210 mImpl->setPrePadding(padding);
2220 return mImpl->getPrePadding();
2237 mImpl->setPostPadding(padding);
2247 return mImpl->getPostPadding();
2261 mImpl->setPaddingMode(paddingMode);
2273 return mImpl->getPaddingMode();
2288 mImpl->setKernelSizeNd(kernelSize);
2298 return mImpl->getKernelSizeNd();
2315 mImpl->setStrideNd(stride);
2325 return mImpl->getStrideNd();
2343 mImpl->setPaddingNd(padding);
2355 return mImpl->getPaddingNd();
2381 mImpl->setDilationNd(dilation);
2391 return mImpl->getDilationNd();
2441 static constexpr int32_t kVALUE = 14;
2478 return mImpl->setOperation(op);
2490 return mImpl->getOperation();
2611 mImpl->setGatherAxis(axis);
2623 return mImpl->getGatherAxis();
2646 mImpl->setNbElementWiseDims(elementWiseDims);
2656 return mImpl->getNbElementWiseDims();
2666 mImpl->setMode(mode);
2676 return mImpl->getMode();
2703 return mImpl->getPlugin();
2730 return mImpl->getPlugin();
2813 mImpl->setOperation(op);
2823 return mImpl->getOperation();
2886 mImpl->setOperation(op);
2896 return mImpl->getOperation();
2906 mImpl->setReduceAxes(reduceAxes);
2916 return mImpl->getReduceAxes();
2926 mImpl->setKeepDimensions(keepDimensions);
2936 return mImpl->getKeepDimensions();
2970 mImpl->setPrePaddingNd(padding);
2982 return mImpl->getPrePaddingNd();
2996 mImpl->setPostPaddingNd(padding);
3008 return mImpl->getPostPaddingNd();
3058 mImpl->setFirstTranspose(permutation);
3070 return mImpl->getFirstTranspose();
3098 mImpl->setReshapeDimensions(dimensions);
3111 return mImpl->getReshapeDimensions();
3158 mImpl->setSecondTranspose(permutation);
3170 return mImpl->getSecondTranspose();
3186 return mImpl->setZeroIsPlaceholder(zeroIsPlaceholder);
3199 return mImpl->getZeroIsPlaceholder();
3310 mImpl->setStart(start);
3325 return mImpl->getStart();
3339 return mImpl->setSize(size);
3354 return mImpl->getSize();
3368 mImpl->setStride(stride);
3383 return mImpl->getStride();
3393 mImpl->setMode(mode);
3403 return mImpl->getMode();
3446 mImpl->setAxes(axes);
3461 return mImpl->getAxes();
3531 mImpl->setOperation(op);
3541 return mImpl->getOperation();
3569 return mImpl->getK();
3579 mImpl->setReduceAxes(reduceAxes);
3589 return mImpl->getReduceAxes();
3691 mImpl->setOperation(index, op);
3703 return mImpl->getOperation(index);
3811 mImpl->setToType(toType);
3822 return mImpl->getToType();
3851 mImpl->setWeights(weights);
3861 return mImpl->getWeights();
3873 mImpl->setDimensions(dimensions);
3885 return mImpl->getDimensions();
3931 static constexpr int32_t kVALUE = 3;
3985 static constexpr int32_t kVALUE = 3;
4015 static constexpr int32_t kVALUE = 2;
4051 static constexpr int32_t kVALUE = 4;
4114 return mImpl->setOutputDimensions(dimensions);
4124 return mImpl->getOutputDimensions();
4152 void setScales(
float const* scales, int32_t nbScales)
noexcept
4154 mImpl->setScales(scales, nbScales);
4171 int32_t
getScales(int32_t size,
float* scales)
const noexcept
4173 return mImpl->getScales(size, scales);
4185 mImpl->setResizeMode(interpolationMode);
4195 return mImpl->getResizeMode();
4230 mImpl->setCoordinateTransformation(coordTransform);
4240 return mImpl->getCoordinateTransformation();
4255 mImpl->setSelectorForSinglePixel(selector);
4265 return mImpl->getSelectorForSinglePixel();
4279 mImpl->setNearestRounding(value);
4289 return mImpl->getNearestRounding();
4311 mImpl->setCubicCoeff(A);
4321 return mImpl->getCubicCoeff();
4334 mImpl->setExcludeOutside(excludeFlag);
4344 return mImpl->getExcludeOutside();
4422 return mBoundary->getLoop();
4427 apiv::VLoopBoundaryLayer* mBoundary;
4445 return mBoundary->getConditional();
4450 apiv::VConditionalBoundaryLayer* mBoundary;
4533 return mImpl->setCondition(condition);
4551 return mImpl->addOutput(trueSubgraphOutput, falseSubgraphOutput);
4563 return mImpl->addInput(input);
4578 mImpl->setName(name);
4588 return mImpl->getName();
4658 return mImpl->getLoopOutput();
4675 mImpl->setAxis(axis);
4683 return mImpl->getAxis();
4732 return mImpl->getTripLimit();
4758 mImpl->setAxis(axis);
4766 return mImpl->getAxis();
4780 mImpl->setReverse(reverse);
4790 return mImpl->getReverse();
4818 return mImpl->addRecurrence(initialValue);
4839 return mImpl->addTripLimit(tensor, limit);
4852 return mImpl->addIterator(tensor, axis, reverse);
4865 return mImpl->addLoopOutput(tensor, outputKind, axis);
4880 mImpl->setName(name);
4890 return mImpl->getName();
4945 mImpl->setMessage(message);
4955 return mImpl->getMessage();
5057 mImpl->setDimensions(dimensions);
5072 return mImpl->getDimensions();
5082 mImpl->setOperation(op);
5092 return mImpl->getOperation();
5111 mImpl->setAlpha(alpha);
5126 return mImpl->getAlpha();
5145 mImpl->setBeta(beta);
5160 return mImpl->getBeta();
5221 mImpl->setAlphaInt64(alpha);
5236 return mImpl->getAlphaInt64();
5255 mImpl->setBetaInt64(beta);
5270 return mImpl->getBetaInt64();
5278 return mImpl->isAlphaBetaInt64();
5295 mImpl->setToType(toType);
5307 return mImpl->getToType();
5401 return mImpl->getAxis();
5412 mImpl->setAxis(axis);
5428 mImpl->setToType(toType);
5440 return mImpl->getToType();
5531 return mImpl->getAxis();
5542 mImpl->setAxis(axis);
5558 mImpl->setToType(toType);
5570 return mImpl->getToType();
5629 return mImpl->setEquation(equation);
5639 return mImpl->getEquation();
5738 mImpl->setMode(mode);
5748 return mImpl->getMode();
5758 mImpl->setAxis(axis);
5766 return mImpl->getAxis();
5810 mImpl->setAxis(axis);
5818 return mImpl->getAxis();
5846 mImpl->setInterpolationMode(mode);
5858 return mImpl->getInterpolationMode();
5868 mImpl->setAlignCorners(alignCorners);
5880 return mImpl->getAlignCorners();
5892 return mImpl->setSampleMode(mode);
5904 return mImpl->getSampleMode();
5998 mImpl->setBoundingBoxFormat(fmt);
6010 return mImpl->getBoundingBoxFormat();
6024 mImpl->setTopKBoxLimit(limit);
6034 return mImpl->getTopKBoxLimit();
6087 mImpl->setBatchAxis(batchAxis);
6097 return mImpl->getBatchAxis();
6110 mImpl->setSequenceAxis(sequenceAxis);
6120 return mImpl->getSequenceAxis();
6158 return mImpl->setEpsilon(eps);
6168 return mImpl->getEpsilon();
6178 return mImpl->setAxes(axesMask);
6188 return mImpl->getAxes();
6209 return mImpl->setNbGroups(nbGroups);
6219 return mImpl->getNbGroups();
6245 return mImpl->setComputePrecision(type);
6255 return mImpl->getComputePrecision();
6323 return mImpl->addInput(name, type, dimensions);
6337 mImpl->markOutput(tensor);
6355 return mImpl->markDebug(tensor);
6371 return mImpl->unmarkDebug(tensor);
6381 return mImpl->isDebugTensor(tensor);
6401 return mImpl->addActivation(input, type);
6420 return mImpl->addLRN(input, window, alpha, beta, k);
6446 return mImpl->addScale(input, mode, shift, scale, power);
6459 return mImpl->addSoftMax(input);
6476 return mImpl->addConcatenation(inputs, nbInputs);
6503 return mImpl->addElementWise(input1, input2, op);
6525 return mImpl->addUnary(input, operation);
6539 return mImpl->addShuffle(input);
6556 return mImpl->addOneHot(indices, values, depth, axis);
6568 return mImpl->getNbLayers();
6582 return mImpl->getLayer(index);
6594 return mImpl->getNbInputs();
6610 return mImpl->getInput(index);
6624 return mImpl->getNbOutputs();
6640 return mImpl->getOutput(index);
6667 return mImpl->addReduce(input, operation, reduceAxes, keepDimensions);
6699 return mImpl->addTopK(input, op, k, reduceAxes);
6715 return mImpl->addGather(data, indices, axis);
6731 return mImpl->addGatherV2(data, indices, mode);
6750 return mImpl->addRaggedSoftMax(input, bounds);
6772 return mImpl->addMatrixMultiply(input0, op0, input1, op1);
6786 return mImpl->addNonZero(input);
6810 return mImpl->addConstant(dimensions, weights);
6824 return mImpl->addIdentity(input);
6839 return mImpl->addCast(input, toType);
6854 mImpl->removeTensor(tensor);
6866 mImpl->unmarkOutput(tensor);
6885 return mImpl->addPluginV2(inputs, nbInputs, plugin);
6902 int32_t nbShapeInputs,
IPluginV3& plugin)
noexcept
6904 return mImpl->addPluginV3(inputs, nbInputs, shapeInputs, nbShapeInputs, plugin);
6923 return mImpl->addSlice(input, start, size, stride);
6947 mImpl->setName(name);
6961 return mImpl->getName();
6977 return mImpl->addShape(input);
6991 return mImpl->hasImplicitBatchDimension();
7001 return mImpl->getFlags();
7013 return mImpl->getFlag(networkDefinitionCreationFlag);
7030 return mImpl->markOutputForShapes(tensor);
7042 return mImpl->unmarkOutputForShapes(tensor);
7060 return mImpl->addParametricReLU(input, slope);
7083 return mImpl->addConvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7102 return mImpl->addPoolingNd(input, type, windowSize);
7125 return mImpl->addDeconvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7162 return mImpl->addScaleNd(input, mode, shift, scale, power, channelAxis);
7178 return mImpl->addResize(input);
7192 return mImpl->addLoop();
7207 return mImpl->addIfConditional();
7246 return mImpl->addSelect(condition, thenInput, elseInput);
7263 return mImpl->addAssertion(condition, message);
7288 return mImpl->addFill(dimensions, op);
7314 return mImpl->addFillV2(dimensions, op, outputType);
7330 return mImpl->addPaddingNd(input, prePadding, postPadding);
7354 return mImpl->setWeightsName(weights, name);
7373 mImpl->setErrorRecorder(recorder);
7388 return mImpl->getErrorRecorder();
7409 return mImpl->addDequantize(input, scale);
7430 return mImpl->addDequantizeV2(input, scale, outputType);
7450 return mImpl->addScatter(data, indices, updates, mode);
7471 return mImpl->addQuantize(input, scale);
7492 return mImpl->addQuantizeV2(input, scale, outputType);
7508 return mImpl->addEinsum(inputs, nbInputs, equation);
7526 return mImpl->addGridSample(input, grid);
7544 return mImpl->addNMS(boxes, scores, maxOutputBoxesPerClass);
7561 return mImpl->addReverseSequence(input, sequenceLens);
7587 return mImpl->addNormalization(input, scale, bias, axesMask);
7598 return mImpl->getBuilder();
7611 return mImpl->markWeightsRefittable(name);
7623 return mImpl->unmarkWeightsRefittable(name);
7636 return mImpl->areWeightsMarkedRefittable(name);
7708 virtual
bool getBatch(
void* bindings[],
char const* names[], int32_t nbBindings) noexcept = 0;
7724 virtual
void const* readCalibrationCache(std::
size_t& length) noexcept = 0;
7734 virtual
void writeCalibrationCache(
void const* ptr, std::
size_t length) noexcept = 0;
7900 virtual
double getRegressionCutoff() const noexcept = 0;
7914 virtual
void const* readHistogramCache(std::
size_t& length) noexcept = 0;
7924 virtual
void writeHistogramCache(
void const* ptr, std::
size_t length) noexcept = 0;
7965 return mImpl->getDataType();
7976 return mImpl->getStrides();
7986 return mImpl->getVectorizedDim();
7997 return mImpl->getComponentsPerElement();
8024 return mImpl->getImplementation();
8032 return mImpl->getTactic();
8058 return mImpl->getName();
8070 return mImpl->getDimensions(index, select);
8078 return mImpl->getNbInputs();
8086 return mImpl->getNbOutputs();
8113 return mImpl->getAlgorithmVariant();
8121 return mImpl->getTimingMSec();
8129 return mImpl->getWorkspaceSize();
8143 return mImpl->getAlgorithmIOInfoByIndex(index);
8178 int32_t nbChoices, int32_t* selection)
noexcept = 0;
8191 int32_t nbAlgorithms)
noexcept = 0;
8283 static constexpr int32_t kVALUE = 2;
8492 return mImpl->serialize();
8516 return mImpl->combine(inputCache, ignoreMismatch);
8526 return mImpl->reset();
8640 static constexpr int32_t kVALUE = 2;
8682 static constexpr int32_t kVALUE = 2;
8721 virtual void phaseStart(
char const* phaseName,
char const* parentPhase, int32_t nbSteps)
noexcept = 0;
8735 virtual bool stepComplete(
char const* phaseName, int32_t step)
noexcept = 0;
8794 virtual
void setAvgTimingIterations(int32_t avgTiming) noexcept
8796 mImpl->setAvgTimingIterations(avgTiming);
8808 return mImpl->getAvgTimingIterations();
8821 mImpl->setEngineCapability(capability);
8833 return mImpl->getEngineCapability();
8845 mImpl->setInt8Calibrator(calibrator);
8855 return mImpl->getInt8Calibrator();
8872 mImpl->setFlags(builderFlags);
8884 return mImpl->getFlags();
8896 mImpl->clearFlag(builderFlag);
8908 mImpl->setFlag(builderFlag);
8920 return mImpl->getFlag(builderFlag);
8937 mImpl->setDeviceType(layer, deviceType);
8947 return mImpl->getDeviceType(layer);
8959 return mImpl->isDeviceTypeSet(layer);
8969 mImpl->resetDeviceType(layer);
8979 return mImpl->canRunOnDLA(layer);
8995 mImpl->setDLACore(dlaCore);
9005 return mImpl->getDLACore();
9016 mImpl->setDefaultDeviceType(deviceType);
9026 return mImpl->getDefaultDeviceType();
9048 return mImpl->setProfileStream(stream);
9060 return mImpl->getProfileStream();
9077 return mImpl->addOptimizationProfile(profile);
9090 return mImpl->getNbOptimizationProfiles();
9102 mImpl->setProfilingVerbosity(verbosity);
9115 return mImpl->getProfilingVerbosity();
9124 mImpl->setAlgorithmSelector(selector);
9132 return mImpl->getAlgorithmSelector();
9150 return mImpl->setCalibrationProfile(profile);
9162 return mImpl->getCalibrationProfile();
9179 mImpl->setQuantizationFlags(flags);
9191 return mImpl->getQuantizationFlags();
9203 mImpl->clearQuantizationFlag(flag);
9215 mImpl->setQuantizationFlag(flag);
9227 return mImpl->getQuantizationFlag(flag);
9249 return mImpl->setTacticSources(tacticSources);
9264 return mImpl->getTacticSources();
9283 return mImpl->createTimingCache(blob, size);
9306 return mImpl->setTimingCache(cache, ignoreMismatch);
9316 return mImpl->getTimingCache();
9348 mImpl->setMemoryPoolLimit(pool, poolSize);
9367 return mImpl->getMemoryPoolLimit(pool);
9385 mImpl->setPreviewFeature(feature, enable);
9399 return mImpl->getPreviewFeature(feature);
9432 mImpl->setBuilderOptimizationLevel(level);
9444 return mImpl->getBuilderOptimizationLevel();
9461 mImpl->setHardwareCompatibilityLevel(hardwareCompatibilityLevel);
9474 return mImpl->getHardwareCompatibilityLevel();
9487 mImpl->setPluginsToSerialize(paths, nbPaths);
9500 return mImpl->getPluginToSerialize(index);
9510 return mImpl->getNbPluginsToSerialize();
9539 mImpl->setMaxAuxStreams(nbStreams);
9549 return mImpl->getMaxAuxStreams();
9565 return mImpl->setProgressMonitor(monitor);
9575 return mImpl->getProgressMonitor();
9591 mImpl->setRuntimePlatform(runtimePlatform);
9603 return mImpl->getRuntimePlatform();
9615 mImpl->setMaxNbTactics(maxNbTactics);
9627 return mImpl->getMaxNbTactics();
9695 return mImpl->platformHasFastFp16();
9705 return mImpl->platformHasFastInt8();
9717 return mImpl->getMaxDLABatchSize();
9725 return mImpl->getNbDLACores();
9742 mImpl->setGpuAllocator(allocator);
9752 return mImpl->createBuilderConfig();
9774 return mImpl->createNetworkV2(flags);
9789 return mImpl->createOptimizationProfile();
9808 mImpl->setErrorRecorder(recorder);
9823 return mImpl->getErrorRecorder();
9841 return mImpl->platformHasTf32();
9860 return mImpl->buildSerializedNetwork(network, config);
9880 return mImpl->buildEngineWithConfig(network, config);
9902 return mImpl->isNetworkSupported(network, config);
9912 return mImpl->getLogger();
9928 return mImpl->setMaxThreads(maxThreads);
9942 return mImpl->getMaxThreads();
9952 return mImpl->getPluginRegistry();
9965extern "C" TENSORRTAPI void* createInferBuilder_INTERNAL(
void* logger, int32_t version)
noexcept;
#define TENSORRTAPI
Definition: NvInferRuntimeBase.h:59
#define NV_TENSORRT_VERSION
Definition: NvInferRuntimeBase.h:91
#define TRT_DEPRECATED
Definition: NvInferRuntimeBase.h:45
#define TRT_DEPRECATED_ENUM
Definition: NvInferRuntimeBase.h:46
Definition: NvInferRuntimeBase.h:200
static constexpr int32_t MAX_DIMS
The maximum rank (number of dimensions) supported for a tensor.
Definition: NvInferRuntimeBase.h:203
An Activation layer in a network definition.
Definition: NvInfer.h:1342
void setBeta(float beta) noexcept
Set the beta parameter (must be finite).
Definition: NvInfer.h:1390
void setActivationType(ActivationType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1351
ActivationType getActivationType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1361
float getAlpha() const noexcept
Get the alpha parameter.
Definition: NvInfer.h:1399
virtual ~IActivationLayer() noexcept=default
float getBeta() const noexcept
Get the beta parameter.
Definition: NvInfer.h:1408
void setAlpha(float alpha) noexcept
Set the alpha parameter (must be finite).
Definition: NvInfer.h:1376
Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorith...
Definition: NvInfer.h:8049
int32_t getNbOutputs() const noexcept
Return number of outputs of the algorithm.
Definition: NvInfer.h:8084
int32_t getNbInputs() const noexcept
Return number of inputs of the algorithm.
Definition: NvInfer.h:8076
char const * getName() const noexcept
Return name of the algorithm node.
Definition: NvInfer.h:8056
virtual ~IAlgorithmContext() noexcept=default
Dims getDimensions(int32_t index, OptProfileSelector select) const noexcept
Get the minimum / optimum / maximum dimensions for input or output tensor.
Definition: NvInfer.h:8068
Describes a variation of execution of a layer. An algorithm is represented by IAlgorithmVariant and t...
Definition: NvInfer.h:8106
std::size_t getWorkspaceSize() const noexcept
The size of the GPU temporary memory in bytes which the algorithm uses at execution time.
Definition: NvInfer.h:8127
float getTimingMSec() const noexcept
The time in milliseconds to execute the algorithm.
Definition: NvInfer.h:8119
IAlgorithmIOInfo const * getAlgorithmIOInfoByIndex(int32_t index) const noexcept
Returns the format of an Algorithm input or output. Algorithm inputs are incrementally numbered first...
Definition: NvInfer.h:8141
virtual ~IAlgorithm() noexcept=default
IAlgorithmVariant const & getAlgorithmVariant() const noexcept
Returns the algorithm variant.
Definition: NvInfer.h:8111
Carries information about input or output of the algorithm. IAlgorithmIOInfo for all the input and ou...
Definition: NvInfer.h:7956
virtual ~IAlgorithmIOInfo() noexcept=default
int64_t getVectorizedDim() const noexcept
Return the index of the vectorized dimension or -1 for non-vectorized formats.
Definition: NvInfer.h:7984
Dims getStrides() const noexcept
Return strides of the input/output tensor of algorithm. For vectorized formats, strides are given in ...
Definition: NvInfer.h:7974
DataType getDataType() const noexcept
Return DataType of the input/output of algorithm.
Definition: NvInfer.h:7963
int64_t getComponentsPerElement() const noexcept
Return the number of components per element. This is always 1 for non-vectorized formats.
Definition: NvInfer.h:7995
provides a unique 128-bit identifier, which along with the input and output information denotes the v...
Definition: NvInfer.h:8017
virtual ~IAlgorithmVariant() noexcept=default
int64_t getTactic() const noexcept
Return tactic of the algorithm.
Definition: NvInfer.h:8030
int64_t getImplementation() const noexcept
Return implementation of the algorithm.
Definition: NvInfer.h:8022
An assertion layer in a network.
Definition: NvInfer.h:4933
void setMessage(char const *message) noexcept
Set the message to print if the assertion fails.
Definition: NvInfer.h:4943
char const * getMessage() const noexcept
Return the assertion message.
Definition: NvInfer.h:4953
virtual ~IAssertionLayer() noexcept=default
Holds properties for configuring a builder to produce an engine.
Definition: NvInfer.h:8782
void setMemoryPoolLimit(MemoryPoolType pool, std::size_t poolSize) noexcept
Set the memory size for the memory pool.
Definition: NvInfer.h:9346
void setQuantizationFlag(QuantizationFlag flag) noexcept
Set a single quantization flag.
Definition: NvInfer.h:9213
nvinfer1::ITimingCache * createTimingCache(void const *blob, std::size_t size) const noexcept
Create timing cache.
Definition: NvInfer.h:9281
void setPreviewFeature(PreviewFeature feature, bool enable) noexcept
Enable or disable a specific preview feature.
Definition: NvInfer.h:9383
TRT_DEPRECATED void setInt8Calibrator(IInt8Calibrator *calibrator) noexcept
Set Int8 Calibration interface.
Definition: NvInfer.h:8843
bool getPreviewFeature(PreviewFeature feature) const noexcept
Get status of preview feature.
Definition: NvInfer.h:9397
void clearQuantizationFlag(QuantizationFlag flag) noexcept
clear a quantization flag.
Definition: NvInfer.h:9201
int32_t getBuilderOptimizationLevel() noexcept
Get builder optimization level.
Definition: NvInfer.h:9442
bool setTacticSources(TacticSources tacticSources) noexcept
Set tactic sources.
Definition: NvInfer.h:9247
void setPluginsToSerialize(char const *const *paths, int32_t nbPaths) noexcept
Set the plugin libraries to be serialized with version-compatible engines.
Definition: NvInfer.h:9485
bool getQuantizationFlag(QuantizationFlag flag) const noexcept
Returns true if the quantization flag is set.
Definition: NvInfer.h:9225
TRT_DEPRECATED IInt8Calibrator * getInt8Calibrator() const noexcept
Get Int8 Calibration interface.
Definition: NvInfer.h:8853
std::size_t getMemoryPoolLimit(MemoryPoolType pool) const noexcept
Get the memory size limit of the memory pool.
Definition: NvInfer.h:9365
int32_t getDLACore() const noexcept
Get the DLA core that the engine executes on.
Definition: NvInfer.h:9003
int32_t getNbPluginsToSerialize() const noexcept
Get the number of plugin library paths to be serialized with version-compatible engines.
Definition: NvInfer.h:9508
void setDeviceType(ILayer const *layer, DeviceType deviceType) noexcept
Set the device that this layer must execute on.
Definition: NvInfer.h:8935
void setEngineCapability(EngineCapability capability) noexcept
Configure the builder to target specified EngineCapability flow.
Definition: NvInfer.h:8819
int32_t getMaxAuxStreams() const noexcept
Get the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9547
bool getFlag(BuilderFlag builderFlag) const noexcept
Returns true if the build mode flag is set.
Definition: NvInfer.h:8918
void setQuantizationFlags(QuantizationFlags flags) noexcept
Set the quantization flags.
Definition: NvInfer.h:9177
void setMaxNbTactics(int32_t maxNbTactics) noexcept
Set the maximum number of tactics to time when there is a choice of tactics.
Definition: NvInfer.h:9613
void setProgressMonitor(IProgressMonitor *monitor) noexcept
Sets the progress monitor for building a network.
Definition: NvInfer.h:9563
void setProfilingVerbosity(ProfilingVerbosity verbosity) noexcept
Set verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:9100
IAlgorithmSelector * getAlgorithmSelector() const noexcept
Get Algorithm Selector.
Definition: NvInfer.h:9130
int32_t getNbOptimizationProfiles() const noexcept
Get number of optimization profiles.
Definition: NvInfer.h:9088
QuantizationFlags getQuantizationFlags() const noexcept
Get the quantization flags.
Definition: NvInfer.h:9189
nvinfer1::ITimingCache const * getTimingCache() const noexcept
Get the pointer to the timing cache from current IBuilderConfig.
Definition: NvInfer.h:9314
void reset() noexcept
Resets the builder configuration to defaults.
Definition: NvInfer.h:9034
bool setTimingCache(ITimingCache const &cache, bool ignoreMismatch) noexcept
Attach a timing cache to IBuilderConfig.
Definition: NvInfer.h:9304
char const * getPluginToSerialize(int32_t index) const noexcept
Get the plugin library path to be serialized with version-compatible engines.
Definition: NvInfer.h:9498
EngineCapability getEngineCapability() const noexcept
Query EngineCapability flow configured for the builder.
Definition: NvInfer.h:8831
void setAlgorithmSelector(IAlgorithmSelector *selector) noexcept
Set Algorithm Selector.
Definition: NvInfer.h:9122
RuntimePlatform getRuntimePlatform() const noexcept
Get the target platform for runtime execution.
Definition: NvInfer.h:9601
DeviceType getDefaultDeviceType() const noexcept
Get the default DeviceType which was set by setDefaultDeviceType.
Definition: NvInfer.h:9024
void setRuntimePlatform(RuntimePlatform runtimePlatform) noexcept
Set the target platform for runtime execution.
Definition: NvInfer.h:9589
int32_t getMaxNbTactics() const noexcept
Query the maximum number of tactics timed when there is a choice.
Definition: NvInfer.h:9625
BuilderFlags getFlags() const noexcept
Get the build mode flags for this builder config. Defaults to 0.
Definition: NvInfer.h:8882
void setFlags(BuilderFlags builderFlags) noexcept
Set the build mode flags to turn on builder options for this network.
Definition: NvInfer.h:8870
TacticSources getTacticSources() const noexcept
Get tactic sources.
Definition: NvInfer.h:9262
void resetDeviceType(ILayer const *layer) noexcept
reset the DeviceType for this layer
Definition: NvInfer.h:8967
void setDLACore(int32_t dlaCore) noexcept
Sets the DLA core used by the network. Defaults to -1.
Definition: NvInfer.h:8993
HardwareCompatibilityLevel getHardwareCompatibilityLevel() const noexcept
Get the hardware compatibility level.
Definition: NvInfer.h:9472
void clearFlag(BuilderFlag builderFlag) noexcept
clear a single build mode flag.
Definition: NvInfer.h:8894
int32_t addOptimizationProfile(IOptimizationProfile const *profile) noexcept
Add an optimization profile.
Definition: NvInfer.h:9075
IProgressMonitor * getProgressMonitor() const noexcept
Definition: NvInfer.h:9573
apiv::VBuilderConfig * mImpl
Definition: NvInfer.h:9631
TRT_DEPRECATED IOptimizationProfile const * getCalibrationProfile() noexcept
Get the current calibration profile.
Definition: NvInfer.h:9160
int32_t getAvgTimingIterations() const noexcept
Query the number of averaging iterations.
Definition: NvInfer.h:8806
void setDefaultDeviceType(DeviceType deviceType) noexcept
Sets the default DeviceType to be used by the builder. It ensures that all the layers that can run on...
Definition: NvInfer.h:9014
void setFlag(BuilderFlag builderFlag) noexcept
Set a single build mode flag.
Definition: NvInfer.h:8906
TRT_DEPRECATED bool setCalibrationProfile(IOptimizationProfile const *profile) noexcept
Add a calibration profile.
Definition: NvInfer.h:9148
virtual ~IBuilderConfig() noexcept=default
DeviceType getDeviceType(ILayer const *layer) const noexcept
Get the device that this layer executes on.
Definition: NvInfer.h:8945
bool canRunOnDLA(ILayer const *layer) const noexcept
Checks if a layer can run on DLA.
Definition: NvInfer.h:8977
cudaStream_t getProfileStream() const noexcept
Get the CUDA stream that is used to profile this network.
Definition: NvInfer.h:9058
void setHardwareCompatibilityLevel(HardwareCompatibilityLevel hardwareCompatibilityLevel) noexcept
Set the hardware compatibility level.
Definition: NvInfer.h:9459
void setMaxAuxStreams(int32_t nbStreams) noexcept
Set the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9537
ProfilingVerbosity getProfilingVerbosity() const noexcept
Get verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:9113
bool isDeviceTypeSet(ILayer const *layer) const noexcept
whether the DeviceType has been explicitly set for this layer
Definition: NvInfer.h:8957
void setBuilderOptimizationLevel(int32_t level) noexcept
Set builder optimization level.
Definition: NvInfer.h:9430
void setProfileStream(const cudaStream_t stream) noexcept
Set the CUDA stream that is used to profile this network.
Definition: NvInfer.h:9046
Builds an engine from a network definition.
Definition: NvInfer.h:9684
int32_t getMaxDLABatchSize() const noexcept
Get the maximum batch size DLA can support. For any tensor the total volume of index dimensions combi...
Definition: NvInfer.h:9715
int32_t getNbDLACores() const noexcept
Return the number of DLA engines available to this builder.
Definition: NvInfer.h:9723
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:9821
apiv::VBuilder * mImpl
Definition: NvInfer.h:9956
ILogger * getLogger() const noexcept
get the logger with which the builder was created
Definition: NvInfer.h:9910
bool isNetworkSupported(INetworkDefinition const &network, IBuilderConfig const &config) const noexcept
Checks that a network is within the scope of the IBuilderConfig settings.
Definition: NvInfer.h:9900
int32_t getMaxThreads() const noexcept
get the maximum number of threads that can be used by the builder.
Definition: NvInfer.h:9940
IPluginRegistry & getPluginRegistry() noexcept
get the local plugin registry that can be used by the builder.
Definition: NvInfer.h:9950
TRT_DEPRECATED bool platformHasFastInt8() const noexcept
Determine whether the platform has fast native int8.
Definition: NvInfer.h:9703
nvinfer1::IOptimizationProfile * createOptimizationProfile() noexcept
Create a new optimization profile.
Definition: NvInfer.h:9787
void setGpuAllocator(IGpuAllocator *allocator) noexcept
Set the GPU allocator.
Definition: NvInfer.h:9740
nvinfer1::INetworkDefinition * createNetworkV2(NetworkDefinitionCreationFlags flags) noexcept
Create a network definition object.
Definition: NvInfer.h:9772
nvinfer1::IBuilderConfig * createBuilderConfig() noexcept
Create a builder configuration object.
Definition: NvInfer.h:9750
void reset() noexcept
Resets the builder state to default values.
Definition: NvInfer.h:9829
bool setMaxThreads(int32_t maxThreads) noexcept
Set the maximum number of threads.
Definition: NvInfer.h:9926
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:9806
nvinfer1::IHostMemory * buildSerializedNetwork(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds and serializes a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:9858
virtual ~IBuilder() noexcept=default
TRT_DEPRECATED bool platformHasTf32() const noexcept
Determine whether the platform has TF32 support.
Definition: NvInfer.h:9839
nvinfer1::ICudaEngine * buildEngineWithConfig(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:9878
A cast layer in a network.
Definition: NvInfer.h:3800
virtual ~ICastLayer() noexcept=default
apiv::VCastLayer * mImpl
Definition: NvInfer.h:3826
DataType getToType() const noexcept
Return cast layer output type.
Definition: NvInfer.h:3820
void setToType(DataType toType) noexcept
Set cast layer output type.
Definition: NvInfer.h:3809
A concatenation layer in a network definition.
Definition: NvInfer.h:2052
void setAxis(int32_t axis) noexcept
Set the axis along which concatenation occurs.
Definition: NvInfer.h:2065
int32_t getAxis() const noexcept
Get the axis along which concatenation occurs.
Definition: NvInfer.h:2075
virtual ~IConcatenationLayer() noexcept=default
This layer represents a condition input to an IIfConditional.
Definition: NvInfer.h:4459
virtual ~IConditionLayer() noexcept=default
Layer that represents a constant value.
Definition: NvInfer.h:3839
void setWeights(Weights weights) noexcept
Set the weights for the layer.
Definition: NvInfer.h:3849
Weights getWeights() const noexcept
Get the weights for the layer.
Definition: NvInfer.h:3859
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions for the layer.
Definition: NvInfer.h:3871
apiv::VConstantLayer * mImpl
Definition: NvInfer.h:3889
virtual ~IConstantLayer() noexcept=default
Dims getDimensions() const noexcept
Get the dimensions for the layer.
Definition: NvInfer.h:3883
A convolution layer in a network definition.
Definition: NvInfer.h:1022
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1147
Weights getBiasWeights() const noexcept
Get the bias weights for the convolution.
Definition: NvInfer.h:1120
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1188
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1292
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the convolution.
Definition: NvInfer.h:1278
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the convolution.
Definition: NvInfer.h:1248
Weights getKernelWeights() const noexcept
Get the kernel weights of the convolution.
Definition: NvInfer.h:1095
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the convolution.
Definition: NvInfer.h:1238
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1302
int64_t getNbOutputMaps() const noexcept
Get the number of output maps for the convolution.
Definition: NvInfer.h:1041
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the convolution.
Definition: NvInfer.h:1085
Dims getPostPadding() const noexcept
Get the post-padding.
Definition: NvInfer.h:1174
int64_t getNbGroups() const noexcept
Get the number of groups of the convolution.
Definition: NvInfer.h:1071
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1200
virtual ~IConvolutionLayer() noexcept=default
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a convolution.
Definition: NvInfer.h:1061
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output maps for the convolution.
Definition: NvInfer.h:1031
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the convolution.
Definition: NvInfer.h:1110
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1223
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the convolution.
Definition: NvInfer.h:1266
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the convolution.
Definition: NvInfer.h:1137
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the convolution.
Definition: NvInfer.h:1164
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1213
An engine for executing inference on a built network, with functionally unsafe features.
Definition: NvInferRuntime.h:2903
A deconvolution layer in a network definition.
Definition: NvInfer.h:2093
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the deconvolution.
Definition: NvInfer.h:2181
int64_t getNbGroups() const noexcept
Get the number of groups for a deconvolution.
Definition: NvInfer.h:2142
Weights getKernelWeights() const noexcept
Get the kernel weights for the deconvolution.
Definition: NvInfer.h:2166
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the deconvolution.
Definition: NvInfer.h:2208
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2323
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2389
Weights getBiasWeights() const noexcept
Get the bias weights for the deconvolution.
Definition: NvInfer.h:2191
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the deconvolution.
Definition: NvInfer.h:2156
int64_t getNbOutputMaps() const noexcept
Get the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2112
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2313
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:2245
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2296
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the deconvolution.
Definition: NvInfer.h:2235
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2286
virtual ~IDeconvolutionLayer() noexcept=default
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2341
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2102
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2353
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2379
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:2259
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a deconvolution.
Definition: NvInfer.h:2132
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:2218
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:2271
A Dequantize layer in a network definition.
Definition: NvInfer.h:5519
void setToType(DataType toType) noexcept
Set the Dequantize layer output type.
Definition: NvInfer.h:5556
virtual ~IDequantizeLayer() noexcept=default
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5529
DataType getToType() const noexcept
Return the Dequantize layer output type.
Definition: NvInfer.h:5568
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5540
An Einsum layer in a network.
Definition: NvInfer.h:5616
bool setEquation(char const *equation) noexcept
Set the equation. The equation is a comma-separated list of subscript labels, where each label refers...
Definition: NvInfer.h:5627
virtual ~IEinsumLayer() noexcept=default
char const * getEquation() const noexcept
Return the equation.
Definition: NvInfer.h:5637
A elementwise layer in a network definition.
Definition: NvInfer.h:2465
virtual ~IElementWiseLayer() noexcept=default
apiv::VElementWiseLayer * mImpl
Definition: NvInfer.h:2494
ElementWiseOperation getOperation() const noexcept
Get the binary operation for the layer.
Definition: NvInfer.h:2488
void setOperation(ElementWiseOperation op) noexcept
Set the binary operation for the layer.
Definition: NvInfer.h:2476
Generate a tensor according to a specified mode.
Definition: NvInfer.h:5044
bool isAlphaBetaInt64() const noexcept
Return true if alpha/beta have type int64, false if they have type double.
Definition: NvInfer.h:5276
FillOperation getOperation() const noexcept
Get the fill operation for the layer.
Definition: NvInfer.h:5090
void setOperation(FillOperation op) noexcept
Set the fill operation for the layer.
Definition: NvInfer.h:5080
DataType getToType() const noexcept
Get the fill layer output type.
Definition: NvInfer.h:5305
void setAlphaInt64(int64_t alpha) noexcept
Set the alpha parameter with int64 datatype.
Definition: NvInfer.h:5219
void setBetaInt64(int64_t beta) noexcept
Set the beta parameter with int64 datatype.
Definition: NvInfer.h:5253
void setBeta(double beta) noexcept
Set the beta parameter.
Definition: NvInfer.h:5143
int64_t getAlphaInt64() const noexcept
Get the value of alpha parameter with int64 datatype.
Definition: NvInfer.h:5234
int64_t getBetaInt64() const noexcept
Get the value of beta parameter with int64 datatype.
Definition: NvInfer.h:5268
double getAlpha() const noexcept
Get the value of alpha parameter.
Definition: NvInfer.h:5124
void setDimensions(Dims const &dimensions) noexcept
Set the output tensor's dimensions.
Definition: NvInfer.h:5055
void setAlpha(double alpha) noexcept
Set the alpha parameter.
Definition: NvInfer.h:5109
void setToType(DataType toType) noexcept
Set the fill layer output type.
Definition: NvInfer.h:5293
Dims getDimensions() const noexcept
Get the output tensor's dimensions.
Definition: NvInfer.h:5070
double getBeta() const noexcept
Get the value of beta parameter.
Definition: NvInfer.h:5158
virtual ~IFillLayer() noexcept=default
A Gather layer in a network definition. Supports several kinds of gathering.
Definition: NvInfer.h:2598
void setGatherAxis(int32_t axis) noexcept
Set the axis used by GatherMode::kELEMENTS and GatherMode::kDEFAULT The axis must be less than the nu...
Definition: NvInfer.h:2609
void setNbElementWiseDims(int32_t elementWiseDims) noexcept
Set the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2644
apiv::VGatherLayer * mImpl
Definition: NvInfer.h:2680
int32_t getNbElementWiseDims() const noexcept
Get the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2654
void setMode(GatherMode mode) noexcept
Set the gather mode.
Definition: NvInfer.h:2664
int32_t getGatherAxis() const noexcept
Get the axis to gather on.
Definition: NvInfer.h:2621
GatherMode getMode() const noexcept
Get the gather mode.
Definition: NvInfer.h:2674
virtual ~IGatherLayer() noexcept=default
A GridSample layer in a network definition.
Definition: NvInfer.h:5837
void setInterpolationMode(InterpolationMode mode) noexcept
Set the grid sample interpolation mode.
Definition: NvInfer.h:5844
bool setSampleMode(SampleMode mode) noexcept
Set the sample mode.
Definition: NvInfer.h:5890
void setAlignCorners(bool alignCorners) noexcept
Set the align corners mode.
Definition: NvInfer.h:5866
apiv::VGridSampleLayer * mImpl
Definition: NvInfer.h:5908
SampleMode getSampleMode() const noexcept
Get the sample mode.
Definition: NvInfer.h:5902
InterpolationMode getInterpolationMode() const noexcept
Get the grid sample interpolation mode.
Definition: NvInfer.h:5856
bool getAlignCorners() const noexcept
Get the align corners mode.
Definition: NvInfer.h:5878
virtual ~IGridSampleLayer() noexcept=default
Class to handle library allocated memory that is accessible to the user.
Definition: NvInferRuntime.h:142
A layer that represents the identity function.
Definition: NvInfer.h:3787
apiv::VIdentityLayer * mImpl
Definition: NvInfer.h:3789
virtual ~IIdentityLayer() noexcept=default
This is a base class for Conditional boundary layers.
Definition: NvInfer.h:4438
IIfConditional * getConditional() const noexcept
Get a pointer to the IIfConditional associated with this boundary layer.
Definition: NvInfer.h:4443
virtual ~IIfConditionalBoundaryLayer() noexcept=default
Helper for constructing conditionally-executed subgraphs.
Definition: NvInfer.h:4520
IIfConditionalInputLayer * addInput(ITensor &input) noexcept
Add an If-conditional input.
Definition: NvInfer.h:4561
char const * getName() const noexcept
Return the name of the conditional.
Definition: NvInfer.h:4586
virtual ~IIfConditional() noexcept=default
IConditionLayer * setCondition(ITensor &condition) noexcept
Set the condition tensor for this If-Conditional construct.
Definition: NvInfer.h:4531
IIfConditionalOutputLayer * addOutput(ITensor &trueSubgraphOutput, ITensor &falseSubgraphOutput) noexcept
Add an If-conditional output.
Definition: NvInfer.h:4549
void setName(char const *name) noexcept
Set the name of the conditional.
Definition: NvInfer.h:4576
This layer represents an output of an IIfConditional.
Definition: NvInfer.h:4476
virtual ~IIfConditionalOutputLayer() noexcept=default
Application-implemented interface for calibration.
Definition: NvInfer.h:7683
virtual TRT_DEPRECATED int32_t getBatchSize() const noexcept=0
Get the batch size used for calibration batches.
A layer to do iterations.
Definition: NvInfer.h:4751
virtual ~IIteratorLayer() noexcept=default
void setReverse(bool reverse) noexcept
Set iteration order to be reverse.
Definition: NvInfer.h:4778
bool getReverse() const noexcept
Check if the iteration order is reverse.
Definition: NvInfer.h:4788
int32_t getAxis() const noexcept
Get axis being iterated over.
Definition: NvInfer.h:4764
void setAxis(int32_t axis) noexcept
Set axis to iterate over.
Definition: NvInfer.h:4756
A LRN layer in a network definition.
Definition: NvInfer.h:1707
int64_t getWindowSize() const noexcept
Get the LRN window size.
Definition: NvInfer.h:1728
float getAlpha() const noexcept
Get the LRN alpha value.
Definition: NvInfer.h:1750
void setWindowSize(int64_t windowSize) noexcept
Set the LRN window size.
Definition: NvInfer.h:1718
void setK(float k) noexcept
Set the LRN K value.
Definition: NvInfer.h:1784
void setAlpha(float alpha) noexcept
Set the LRN alpha value.
Definition: NvInfer.h:1740
void setBeta(float beta) noexcept
Set the LRN beta value.
Definition: NvInfer.h:1762
virtual ~ILRNLayer() noexcept=default
float getBeta() const noexcept
Get the LRN beta value.
Definition: NvInfer.h:1772
float getK() const noexcept
Get the LRN K value.
Definition: NvInfer.h:1794
Base class for all layer classes in a network definition.
Definition: NvInfer.h:550
bool precisionIsSet() const noexcept
whether the computational precision has been set for this layer
Definition: NvInfer.h:692
void setMetadata(char const *metadata) noexcept
Set the metadata for this layer.
Definition: NvInfer.h:808
void setPrecision(DataType dataType) noexcept
Set the preferred or required computational precision of this layer in a weakly-typed network.
Definition: NvInfer.h:668
void setName(char const *name) noexcept
Set the name of a layer.
Definition: NvInfer.h:571
void resetPrecision() noexcept
reset the computational precision for this layer
Definition: NvInfer.h:702
int32_t getNbInputs() const noexcept
Get the number of inputs of a layer.
Definition: NvInfer.h:589
char const * getMetadata() const noexcept
Get the metadata of the layer.
Definition: NvInfer.h:821
DataType getOutputType(int32_t index) const noexcept
get the output type of this layer
Definition: NvInfer.h:764
DataType getPrecision() const noexcept
get the computational precision of this layer
Definition: NvInfer.h:680
char const * getName() const noexcept
Return the name of a layer.
Definition: NvInfer.h:581
int32_t getNbOutputs() const noexcept
Get the number of outputs of a layer.
Definition: NvInfer.h:610
bool outputTypeIsSet(int32_t index) const noexcept
whether the output type has been set for this layer
Definition: NvInfer.h:778
ITensor * getOutput(int32_t index) const noexcept
Get the layer output corresponding to the given index.
Definition: NvInfer.h:620
void setInput(int32_t index, ITensor &tensor) noexcept
Replace an input of this layer with a specific tensor.
Definition: NvInfer.h:637
void resetOutputType(int32_t index) noexcept
reset the output type for this layer
Definition: NvInfer.h:790
ITensor * getInput(int32_t index) const noexcept
Get the layer input corresponding to the given index.
Definition: NvInfer.h:602
void setOutputType(int32_t index, DataType dataType) noexcept
Set the output type of this layer in a weakly-typed network.
Definition: NvInfer.h:749
LayerType getType() const noexcept
Return the type of a layer.
Definition: NvInfer.h:557
virtual ~ILayer() noexcept=default
Application-implemented logging interface for the builder, refitter and runtime.
Definition: NvInferRuntime.h:1464
This is a base class for Loop boundary layers.
Definition: NvInfer.h:4415
virtual ~ILoopBoundaryLayer() noexcept=default
ILoop * getLoop() const noexcept
Get a pointer to ILoop associated with this boundary layer.
Definition: NvInfer.h:4420
Helper for creating a recurrent subgraph.
Definition: NvInfer.h:4808
void setName(char const *name) noexcept
Set the name of the loop.
Definition: NvInfer.h:4878
ITripLimitLayer * addTripLimit(ITensor &tensor, TripLimit limit) noexcept
Add a trip-count limiter, based on the given tensor.
Definition: NvInfer.h:4837
IIteratorLayer * addIterator(ITensor &tensor, int32_t axis=0, bool reverse=false) noexcept
Return layer that subscripts tensor by loop iteration.
Definition: NvInfer.h:4850
ILoopOutputLayer * addLoopOutput(ITensor &tensor, LoopOutput outputKind, int32_t axis=0) noexcept
Make an output for this loop, based on the given tensor.
Definition: NvInfer.h:4863
virtual ~ILoop() noexcept=default
char const * getName() const noexcept
Return the name of the loop.
Definition: NvInfer.h:4888
IRecurrenceLayer * addRecurrence(ITensor &initialValue) noexcept
Create a recurrence layer for this loop with initialValue as its first input.
Definition: NvInfer.h:4816
An ILoopOutputLayer is the sole way to get output from a loop.
Definition: NvInfer.h:4651
virtual ~ILoopOutputLayer() noexcept=default
int32_t getAxis() const noexcept
Get axis being concatenated over.
Definition: NvInfer.h:4681
LoopOutput getLoopOutput() const noexcept
Get which kind a loop output has.
Definition: NvInfer.h:4656
void setAxis(int32_t axis) noexcept
Set where to insert the contenation axis. Ignored if getLoopOutput() is kLAST_VALUE.
Definition: NvInfer.h:4673
Layer that represents a Matrix Multiplication.
Definition: NvInfer.h:3679
apiv::VMatrixMultiplyLayer * mImpl
Definition: NvInfer.h:3707
virtual ~IMatrixMultiplyLayer() noexcept=default
MatrixOperation getOperation(int32_t index) const noexcept
Get the operation for an input tensor.
Definition: NvInfer.h:3701
void setOperation(int32_t index, MatrixOperation op) noexcept
Set the operation for an input tensor.
Definition: NvInfer.h:3689
A non-maximum suppression layer in a network definition.
Definition: NvInfer.h:5985
virtual ~INMSLayer() noexcept=default
void setTopKBoxLimit(int32_t limit) noexcept
Set the TopK box limit parameter for the layer.
Definition: NvInfer.h:6022
void setBoundingBoxFormat(BoundingBoxFormat fmt) noexcept
Set the bounding box format parameter for the layer.
Definition: NvInfer.h:5996
BoundingBoxFormat getBoundingBoxFormat() const noexcept
Get the bounding box format parameter for the layer.
Definition: NvInfer.h:6008
apiv::VNMSLayer * mImpl
Definition: NvInfer.h:6058
int32_t getTopKBoxLimit() const noexcept
Get the TopK box limit parameter for the layer.
Definition: NvInfer.h:6032
A network definition for input to the builder.
Definition: NvInfer.h:6281
IPluginV2Layer * addPluginV2(ITensor *const *inputs, int32_t nbInputs, IPluginV2 &plugin) noexcept
Add a plugin layer to the network using the IPluginV2 interface.
Definition: NvInfer.h:6883
IConcatenationLayer * addConcatenation(ITensor *const *inputs, int32_t nbInputs) noexcept
Add a concatenation layer to the network.
Definition: NvInfer.h:6474
IShuffleLayer * addShuffle(ITensor &input) noexcept
Add a shuffle layer to the network.
Definition: NvInfer.h:6537
INormalizationLayer * addNormalization(ITensor &input, ITensor &scale, ITensor &bias, uint32_t axesMask) noexcept
Add a normalization layer to the network.
Definition: NvInfer.h:7585
void setName(char const *name) noexcept
Sets the name of the network.
Definition: NvInfer.h:6945
bool markDebug(ITensor &tensor) noexcept
Mark a tensor as a debug tensor.
Definition: NvInfer.h:6353
ILRNLayer * addLRN(ITensor &input, int64_t window, float alpha, float beta, float k) noexcept
Add a LRN layer to the network.
Definition: NvInfer.h:6418
ITopKLayer * addTopK(ITensor &input, TopKOperation op, int32_t k, uint32_t reduceAxes) noexcept
Add a TopK layer to the network.
Definition: NvInfer.h:6697
IAssertionLayer * addAssertion(ITensor &condition, char const *message) noexcept
Add an assertion layer to the network.
Definition: NvInfer.h:7261
IConvolutionLayer * addConvolutionNd(ITensor &input, int64_t nbOutputMaps, Dims const &kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a multi-dimension convolution layer to the network.
Definition: NvInfer.h:7080
ICastLayer * addCast(ITensor &input, DataType toType) noexcept
Add a cast layer.
Definition: NvInfer.h:6837
IScaleLayer * addScaleNd(ITensor &input, ScaleMode mode, Weights shift, Weights scale, Weights power, int32_t channelAxis) noexcept
Add a multi-dimension scale layer to the network.
Definition: NvInfer.h:7159
char const * getName() const noexcept
Returns the name associated with the network.
Definition: NvInfer.h:6959
IParametricReLULayer * addParametricReLU(ITensor &input, ITensor &slope) noexcept
Add a parametric ReLU layer to the network.
Definition: NvInfer.h:7058
ITensor * getOutput(int32_t index) const noexcept
Get the output tensor specified by the given index.
Definition: NvInfer.h:6638
ITensor * getInput(int32_t index) const noexcept
Get the input tensor specified by the given index.
Definition: NvInfer.h:6608
IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7428
bool unmarkOutputForShapes(ITensor &tensor) noexcept
Undo markOutputForShapes.
Definition: NvInfer.h:7040
IFillLayer * addFill(Dims const &dimensions, FillOperation op, DataType outputType) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7312
ILoop * addLoop() noexcept
Add a loop to the network.
Definition: NvInfer.h:7190
IActivationLayer * addActivation(ITensor &input, ActivationType type) noexcept
Add an activation layer to the network.
Definition: NvInfer.h:6399
TRT_DEPRECATED IFillLayer * addFill(Dims const &dimensions, FillOperation op) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7286
ISliceLayer * addSlice(ITensor &input, Dims const &start, Dims const &size, Dims const &stride) noexcept
Add a slice layer to the network.
Definition: NvInfer.h:6921
virtual ~INetworkDefinition() noexcept=default
TRT_DEPRECATED IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7469
virtual IBuilder & getBuilder() const noexcept
Return the builder from which this INetworkDefinition was created.
Definition: NvInfer.h:7596
INMSLayer * addNMS(ITensor &boxes, ITensor &scores, ITensor &maxOutputBoxesPerClass) noexcept
Add a non-maximum suppression layer to the network.
Definition: NvInfer.h:7542
ILayer * getLayer(int32_t index) const noexcept
Get the layer specified by the given index.
Definition: NvInfer.h:6580
bool getFlag(NetworkDefinitionCreationFlag networkDefinitionCreationFlag) const noexcept
Returns true if the network definition creation flag is set.
Definition: NvInfer.h:7011
IIfConditional * addIfConditional() noexcept
Add an if-then-else to the network.
Definition: NvInfer.h:7205
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:7386
IReverseSequenceLayer * addReverseSequence(ITensor &input, ITensor &sequenceLens) noexcept
Add a ReverseSequence layer to the network.
Definition: NvInfer.h:7559
int32_t getNbInputs() const noexcept
Get the number of inputs in the network.
Definition: NvInfer.h:6592
NetworkDefinitionCreationFlags getFlags() const noexcept
Get the network definition creation flags for this network definition object. Defaults to 0.
Definition: NvInfer.h:6999
IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7490
IReduceLayer * addReduce(ITensor &input, ReduceOperation operation, uint32_t reduceAxes, bool keepDimensions) noexcept
Add a reduce layer to the network.
Definition: NvInfer.h:6664
IUnaryLayer * addUnary(ITensor &input, UnaryOperation operation) noexcept
Add a unary layer to the network.
Definition: NvInfer.h:6523
IGridSampleLayer * addGridSample(ITensor &input, ITensor &grid) noexcept
Add a GridSample layer to the network.
Definition: NvInfer.h:7524
void removeTensor(ITensor &tensor) noexcept
remove a tensor from the network definition.
Definition: NvInfer.h:6852
bool areWeightsMarkedRefittable(char const *name) const noexcept
Whether the weight has been marked as refittable.
Definition: NvInfer.h:7634
ISelectLayer * addSelect(ITensor &condition, ITensor &thenInput, ITensor &elseInput) noexcept
Add a select layer to the network.
Definition: NvInfer.h:7244
IScatterLayer * addScatter(ITensor &data, ITensor &indices, ITensor &updates, ScatterMode mode) noexcept
Add a Scatter layer to the network with specified mode and axis=0.
Definition: NvInfer.h:7448
int32_t getNbLayers() const noexcept
Get the number of layers in the network.
Definition: NvInfer.h:6566
TRT_DEPRECATED bool hasImplicitBatchDimension() const noexcept
Query whether the network was created with an implicit batch dimension.
Definition: NvInfer.h:6989
apiv::VNetworkDefinition * mImpl
Definition: NvInfer.h:7640
bool markOutputForShapes(ITensor &tensor) noexcept
Enable tensor's value to be computed by IExecutionContext::getShapeBinding.
Definition: NvInfer.h:7028
IOneHotLayer * addOneHot(ITensor &indices, ITensor &values, ITensor &depth, int32_t axis) noexcept
Add a OneHot layer to the network.
Definition: NvInfer.h:6554
IScaleLayer * addScale(ITensor &input, ScaleMode mode, Weights shift, Weights scale, Weights power) noexcept
Add a Scale layer to the network.
Definition: NvInfer.h:6444
IPluginV3Layer * addPluginV3(ITensor *const *inputs, int32_t nbInputs, ITensor *const *shapeInputs, int32_t nbShapeInputs, IPluginV3 &plugin) noexcept
Add a plugin layer implementing the IPluginV3 interface to the network.
Definition: NvInfer.h:6901
void unmarkOutput(ITensor &tensor) noexcept
unmark a tensor as a network output.
Definition: NvInfer.h:6864
IIdentityLayer * addIdentity(ITensor &input) noexcept
Add an identity layer.
Definition: NvInfer.h:6822
IGatherLayer * addGatherV2(ITensor &data, ITensor &indices, GatherMode mode) noexcept
Add gather with specified mode, axis=0 and nbElementWiseDims=0.
Definition: NvInfer.h:6729
IElementWiseLayer * addElementWise(ITensor &input1, ITensor &input2, ElementWiseOperation op) noexcept
Add an elementwise layer to the network.
Definition: NvInfer.h:6501
IConstantLayer * addConstant(Dims const &dimensions, Weights weights) noexcept
Add a constant layer to the network.
Definition: NvInfer.h:6808
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:7371
IPoolingLayer * addPoolingNd(ITensor &input, PoolingType type, Dims const &windowSize) noexcept
Add a multi-dimension pooling layer to the network.
Definition: NvInfer.h:7100
IRaggedSoftMaxLayer * addRaggedSoftMax(ITensor &input, ITensor &bounds) noexcept
Add a RaggedSoftMax layer to the network.
Definition: NvInfer.h:6748
IShapeLayer * addShape(ITensor &input) noexcept
Add a shape layer to the network.
Definition: NvInfer.h:6975
IGatherLayer * addGather(ITensor &data, ITensor &indices, int32_t axis) noexcept
Add gather with mode GatherMode::kDEFAULT and specified axis and nbElementWiseDims=0.
Definition: NvInfer.h:6713
bool unmarkWeightsRefittable(char const *name) noexcept
Unmark weights as refittable when the builder flag kREFIT_INDIVIDUAL is set.
Definition: NvInfer.h:7621
bool markWeightsRefittable(char const *name) noexcept
Mark weights as refittable when the builder flag kREFIT_INDIVIDUAL is set.
Definition: NvInfer.h:7609
IDeconvolutionLayer * addDeconvolutionNd(ITensor &input, int64_t nbOutputMaps, Dims kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a multi-dimension deconvolution layer to the network.
Definition: NvInfer.h:7122
IResizeLayer * addResize(ITensor &input) noexcept
Add a resize layer to the network.
Definition: NvInfer.h:7176
IMatrixMultiplyLayer * addMatrixMultiply(ITensor &input0, MatrixOperation op0, ITensor &input1, MatrixOperation op1) noexcept
Add a MatrixMultiply layer to the network.
Definition: NvInfer.h:6769
ISoftMaxLayer * addSoftMax(ITensor &input) noexcept
Add a SoftMax layer to the network.
Definition: NvInfer.h:6457
bool isDebugTensor(nvinfer1::ITensor const &tensor) const noexcept
Check if a tensor is marked as debug tensor.
Definition: NvInfer.h:6379
bool unmarkDebug(ITensor &tensor) noexcept
Unmark a tensor as a debug tensor.
Definition: NvInfer.h:6369
IEinsumLayer * addEinsum(ITensor *const *inputs, int32_t nbInputs, char const *equation) noexcept
Add an Einsum layer to the network.
Definition: NvInfer.h:7506
void markOutput(ITensor &tensor) noexcept
Mark a tensor as a network output.
Definition: NvInfer.h:6335
IPaddingLayer * addPaddingNd(ITensor &input, Dims const &prePadding, Dims const &postPadding) noexcept
Add a padding layer to the network. Only 2D padding is currently supported.
Definition: NvInfer.h:7328
INonZeroLayer * addNonZero(ITensor &input) noexcept
Add a nonzero layer to the network.
Definition: NvInfer.h:6784
TRT_DEPRECATED IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7407
int32_t getNbOutputs() const noexcept
Get the number of outputs in the network.
Definition: NvInfer.h:6622
bool setWeightsName(Weights weights, char const *name) noexcept
Associate a name with all current uses of the given weights.
Definition: NvInfer.h:7352
Forward declaration of IEngineInspector for use by other interfaces.
Definition: NvInferRuntime.h:51
Definition: NvInfer.h:3733
virtual ~INonZeroLayer() noexcept=default
A normalization layer in a network definition.
Definition: NvInfer.h:6147
float getEpsilon() const noexcept
Get the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6166
uint32_t getAxes() const noexcept
Get the axes value used for the normalization calculation.
Definition: NvInfer.h:6186
virtual ~INormalizationLayer() noexcept=default
void setEpsilon(float eps) noexcept
Set the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6156
DataType getComputePrecision() const noexcept
Get the compute precision of this layer.
Definition: NvInfer.h:6253
apiv::VNormalizationLayer * mImpl
Definition: NvInfer.h:6259
int64_t getNbGroups() const noexcept
Get the number of groups used to split the channels for the normalization calculation.
Definition: NvInfer.h:6217
void setAxes(uint32_t axesMask) noexcept
Set the reduction axes for the normalization calculation.
Definition: NvInfer.h:6176
void setComputePrecision(DataType type) noexcept
Set the compute precision of this layer.
Definition: NvInfer.h:6243
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups used to split the channels in the normalization calculation.
Definition: NvInfer.h:6207
A OneHot layer in a network definition.
Definition: NvInfer.h:5801
apiv::VOneHotLayer * mImpl
Definition: NvInfer.h:5822
void setAxis(int32_t axis) noexcept
Set the axis parameter.
Definition: NvInfer.h:5808
int32_t getAxis() const noexcept
Get the value of the axis parameter.
Definition: NvInfer.h:5816
Optimization profile for dynamic input dimensions and shape tensors.
Definition: NvInferRuntime.h:2517
Layer that represents a padding operation.
Definition: NvInfer.h:2957
Dims getPostPaddingNd() const noexcept
Get the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3006
void setPrePaddingNd(Dims const &padding) noexcept
Set the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2968
virtual ~IPaddingLayer() noexcept=default
void setPostPaddingNd(Dims const &padding) noexcept
Set the padding that is applied at the end of the tensor.
Definition: NvInfer.h:2994
Dims getPrePaddingNd() const noexcept
Get the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2980
apiv::VPaddingLayer * mImpl
Definition: NvInfer.h:3012
Layer that represents a parametric ReLU operation.
Definition: NvInfer.h:3903
apiv::VParametricReLULayer * mImpl
Definition: NvInfer.h:3905
virtual ~IParametricReLULayer() noexcept=default
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferRuntimeCommon.h:56
Plugin class for user-implemented layers.
Definition: NvInferRuntimePlugin.h:134
Layer type for pluginV2.
Definition: NvInfer.h:2694
virtual ~IPluginV2Layer() noexcept=default
apiv::VPluginV2Layer * mImpl
Definition: NvInfer.h:2707
IPluginV2 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:2701
Layer type for V3 plugins.
Definition: NvInfer.h:2721
virtual ~IPluginV3Layer() noexcept=default
IPluginV3 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:2728
apiv::VPluginV3Layer * mImpl
Definition: NvInfer.h:2734
A Pooling layer in a network definition.
Definition: NvInfer.h:1456
PoolingType getPoolingType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1475
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1608
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:1584
bool getAverageCountExcludesPadding() const noexcept
Get whether average pooling uses as a denominator the overlap area between the window and the unpadde...
Definition: NvInfer.h:1528
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1556
void setPoolingType(PoolingType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1465
void setWindowSizeNd(Dims const &windowSize) noexcept
Set the multi-dimension window size for pooling.
Definition: NvInfer.h:1621
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1597
Dims getWindowSizeNd() const noexcept
Get the multi-dimension window size for pooling.
Definition: NvInfer.h:1631
void setAverageCountExcludesPadding(bool exclusive) noexcept
Set whether average pooling uses as a denominator the overlap area between the window and the unpadde...
Definition: NvInfer.h:1517
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding for pooling.
Definition: NvInfer.h:1675
float getBlendFactor() const noexcept
Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1503
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride for pooling.
Definition: NvInfer.h:1646
Dims getStrideNd() const noexcept
Get the multi-dimension stride for pooling.
Definition: NvInfer.h:1656
virtual ~IPoolingLayer() noexcept=default
Dims getPaddingNd() const noexcept
Get the multi-dimension padding for pooling.
Definition: NvInfer.h:1687
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding for pooling.
Definition: NvInfer.h:1574
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding for pooling.
Definition: NvInfer.h:1546
void setBlendFactor(float blendFactor) noexcept
Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1490
A Quantize layer in a network definition.
Definition: NvInfer.h:5389
void setToType(DataType toType) noexcept
Set the Quantize layer output type.
Definition: NvInfer.h:5426
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5410
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5399
virtual ~IQuantizeLayer() noexcept=default
DataType getToType() const noexcept
Return the Quantize layer output type.
Definition: NvInfer.h:5438
A RaggedSoftmax layer in a network definition.
Definition: NvInfer.h:3754
apiv::VRaggedSoftMaxLayer * mImpl
Definition: NvInfer.h:3756
virtual ~IRaggedSoftMaxLayer() noexcept=default
A recurrence layer in a network definition.
Definition: NvInfer.h:4604
virtual ~IRecurrenceLayer() noexcept=default
Layer that represents a reduction across a non-bool tensor.
Definition: NvInfer.h:2877
void setKeepDimensions(bool keepDimensions) noexcept
Set the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2924
void setOperation(ReduceOperation op) noexcept
Set the reduce operation for the layer.
Definition: NvInfer.h:2884
ReduceOperation getOperation() const noexcept
Get the reduce operation for the layer.
Definition: NvInfer.h:2894
virtual ~IReduceLayer() noexcept=default
uint32_t getReduceAxes() const noexcept
Get the axes over which to reduce for the layer.
Definition: NvInfer.h:2914
void setReduceAxes(uint32_t reduceAxes) noexcept
Set the axes over which to reduce.
Definition: NvInfer.h:2904
apiv::VReduceLayer * mImpl
Definition: NvInfer.h:2940
bool getKeepDimensions() const noexcept
Get the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2934
A resize layer in a network definition.
Definition: NvInfer.h:4092
void setSelectorForSinglePixel(ResizeSelector selector) noexcept
Set coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4253
void setNearestRounding(ResizeRoundMode value) noexcept
Set rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4277
virtual ~IResizeLayer() noexcept=default
int32_t getScales(int32_t size, float *scales) const noexcept
Copies resize scales to scales[0, ..., nbScales-1], where nbScales is the number of scales that were ...
Definition: NvInfer.h:4171
void setOutputDimensions(Dims const &dimensions) noexcept
Set the output dimensions.
Definition: NvInfer.h:4112
void setCubicCoeff(float A) noexcept
Set the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4309
void setScales(float const *scales, int32_t nbScales) noexcept
Set the resize scales.
Definition: NvInfer.h:4152
float getCubicCoeff() const noexcept
Get the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4319
ResizeSelector getSelectorForSinglePixel() const noexcept
Get the coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4263
InterpolationMode getResizeMode() const noexcept
Get resize mode for an input tensor.
Definition: NvInfer.h:4193
void setCoordinateTransformation(ResizeCoordinateTransformation coordTransform) noexcept
Set coordinate transformation function.
Definition: NvInfer.h:4228
void setExcludeOutside(bool excludeFlag) noexcept
Set the state for excluding outside pixels.
Definition: NvInfer.h:4332
void setResizeMode(InterpolationMode interpolationMode) noexcept
Set resize mode for an input tensor.
Definition: NvInfer.h:4183
Dims getOutputDimensions() const noexcept
Get the output dimensions.
Definition: NvInfer.h:4122
ResizeRoundMode getNearestRounding() const noexcept
Get rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4287
bool getExcludeOutside() const noexcept
Get the state for excluding outside pixels.
Definition: NvInfer.h:4342
ResizeCoordinateTransformation getCoordinateTransformation() const noexcept
Get coordinate transformation function.
Definition: NvInfer.h:4238
A ReverseSequence layer in a network definition.
Definition: NvInfer.h:6075
void setSequenceAxis(int32_t sequenceAxis) noexcept
Set the sequence axis. Default is 0.
Definition: NvInfer.h:6108
int32_t getBatchAxis() const noexcept
Return the batch axis. Return 1 if no batch axis was set.
Definition: NvInfer.h:6095
apiv::VReverseSequenceLayer * mImpl
Definition: NvInfer.h:6124
int32_t getSequenceAxis() const noexcept
Return the sequence axis. Return 0 if no sequence axis was set.
Definition: NvInfer.h:6118
void setBatchAxis(int32_t batchAxis) noexcept
Set the batch axis. Default is 1.
Definition: NvInfer.h:6085
virtual ~IReverseSequenceLayer() noexcept=default
A Scale layer in a network definition.
Definition: NvInfer.h:1853
Weights getScale() const noexcept
Get the scale value.
Definition: NvInfer.h:1910
Weights getPower() const noexcept
Get the power value.
Definition: NvInfer.h:1930
void setScale(Weights scale) noexcept
Set the scale value.
Definition: NvInfer.h:1900
void setPower(Weights power) noexcept
Set the power value.
Definition: NvInfer.h:1920
ScaleMode getMode() const noexcept
Get the scale mode.
Definition: NvInfer.h:1870
void setShift(Weights shift) noexcept
Set the shift value.
Definition: NvInfer.h:1880
void setChannelAxis(int32_t channelAxis) noexcept
Set the channel axis.
Definition: NvInfer.h:1966
Weights getShift() const noexcept
Get the shift value.
Definition: NvInfer.h:1890
virtual ~IScaleLayer() noexcept=default
void setMode(ScaleMode mode) noexcept
Set the scale mode.
Definition: NvInfer.h:1860
int32_t getChannelAxis() const noexcept
Get the channel axis.
Definition: NvInfer.h:1945
A scatter layer in a network definition. Supports several kinds of scattering.
Definition: NvInfer.h:5729
void setMode(ScatterMode mode) noexcept
Set the scatter mode.
Definition: NvInfer.h:5736
apiv::VScatterLayer * mImpl
Definition: NvInfer.h:5770
void setAxis(int32_t axis) noexcept
Set the axis used by ScatterMode::kELEMENTS.
Definition: NvInfer.h:5756
int32_t getAxis() const noexcept
Get the axis.
Definition: NvInfer.h:5764
ScatterMode getMode() const noexcept
Get the scatter mode.
Definition: NvInfer.h:5746
virtual ~IScatterLayer() noexcept=default
Select elements from two data tensors based on a condition tensor.
Definition: NvInfer.h:4911
virtual ~ISelectLayer() noexcept=default
Layer type for getting shape of a tensor.
Definition: NvInfer.h:3482
virtual ~IShapeLayer() noexcept=default
apiv::VShapeLayer * mImpl
Definition: NvInfer.h:3484
Layer type for shuffling data.
Definition: NvInfer.h:3045
apiv::VShuffleLayer * mImpl
Definition: NvInfer.h:3203
void setFirstTranspose(Permutation permutation) noexcept
Set the permutation applied by the first transpose operation.
Definition: NvInfer.h:3056
void setSecondTranspose(Permutation permutation) noexcept
Set the permutation applied by the second transpose operation.
Definition: NvInfer.h:3156
Dims getReshapeDimensions() const noexcept
Get the reshaped dimensions.
Definition: NvInfer.h:3109
void setReshapeDimensions(Dims const &dimensions) noexcept
Set the reshaped dimensions.
Definition: NvInfer.h:3096
Permutation getFirstTranspose() const noexcept
Get the permutation applied by the first transpose operation.
Definition: NvInfer.h:3068
virtual ~IShuffleLayer() noexcept=default
Permutation getSecondTranspose() const noexcept
Get the permutation applied by the second transpose operation.
Definition: NvInfer.h:3168
bool getZeroIsPlaceholder() const noexcept
Get meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3197
void setZeroIsPlaceholder(bool zeroIsPlaceholder) noexcept
Set meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3184
Slices an input tensor into an output tensor based on the offset and strides.
Definition: NvInfer.h:3297
void setStride(Dims const &stride) noexcept
Set the stride for computing the output slice data.
Definition: NvInfer.h:3366
apiv::VSliceLayer * mImpl
Definition: NvInfer.h:3465
virtual ~ISliceLayer() noexcept=default
void setSize(Dims const &size) noexcept
Set the dimensions of the output slice.
Definition: NvInfer.h:3337
void setAxes(Dims const &axes) noexcept
Set the axes for this ISliceLayer.
Definition: NvInfer.h:3444
void setStart(Dims const &start) noexcept
Set the start offset that the slice layer uses to create the output slice.
Definition: NvInfer.h:3308
Dims getStart() const noexcept
Get the start offset for the slice layer.
Definition: NvInfer.h:3323
void setMode(SampleMode mode) noexcept
Set the slice mode.
Definition: NvInfer.h:3391
Dims getSize() const noexcept
Get dimensions of the output slice.
Definition: NvInfer.h:3352
SampleMode getMode() const noexcept
Get the slice mode.
Definition: NvInfer.h:3401
Dims getStride() const noexcept
Get the stride for the output slice.
Definition: NvInfer.h:3381
Dims getAxes() const noexcept
Get the axes for this ISliceLayer.
Definition: NvInfer.h:3459
A Softmax layer in a network definition.
Definition: NvInfer.h:1997
void setAxes(uint32_t axes) noexcept
Set the axis along which softmax is computed. Currently, only one axis can be set.
Definition: NvInfer.h:2019
uint32_t getAxes() const noexcept
Get the axis along which softmax occurs.
Definition: NvInfer.h:2029
virtual ~ISoftMaxLayer() noexcept=default
A tensor in a network definition.
Definition: NvInfer.h:181
void setAllowedFormats(TensorFormats formats) noexcept
Set allowed formats for an input or output tensor. By default all formats are allowed....
Definition: NvInfer.h:426
TensorLocation getLocation() const noexcept
Get the storage location of a tensor.
Definition: NvInfer.h:345
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions of a tensor.
Definition: NvInfer.h:228
void resetDynamicRange() noexcept
Undo effect of setDynamicRange.
Definition: NvInfer.h:384
void setName(char const *name) noexcept
Set the tensor name.
Definition: NvInfer.h:197
bool isExecutionTensor() const noexcept
Whether the tensor is an execution tensor.
Definition: NvInfer.h:491
void setType(DataType type) noexcept
Set the data type of a tensor.
Definition: NvInfer.h:257
bool dynamicRangeIsSet() const noexcept
Query whether dynamic range is set.
Definition: NvInfer.h:376
char const * getName() const noexcept
Get the tensor name.
Definition: NvInfer.h:209
bool isShapeTensor() const noexcept
Whether the tensor is a shape tensor.
Definition: NvInfer.h:470
float getDynamicRangeMax() const noexcept
Get maximum of dynamic range.
Definition: NvInfer.h:404
bool isNetworkInput() const noexcept
Whether the tensor is a network input.
Definition: NvInfer.h:294
TRT_DEPRECATED void setBroadcastAcrossBatch(bool broadcastAcrossBatch) noexcept
Set whether to enable broadcast of tensor across the implicit batch dimension.
Definition: NvInfer.h:319
TRT_DEPRECATED bool setDynamicRange(float min, float max) noexcept
Set dynamic range for the tensor.
Definition: NvInfer.h:286
TRT_DEPRECATED bool getBroadcastAcrossBatch() const noexcept
Check if tensor is broadcast across the implicit batch dimension.
Definition: NvInfer.h:333
bool isNetworkOutput() const noexcept
Whether the tensor is a network output.
Definition: NvInfer.h:302
DataType getType() const noexcept
Get the data type of a tensor.
Definition: NvInfer.h:269
apiv::VTensor * mImpl
Definition: NvInfer.h:538
float getDynamicRangeMin() const noexcept
Get minimum of dynamic range.
Definition: NvInfer.h:394
virtual ~ITensor() noexcept=default
void setDimensionName(int32_t index, char const *name) noexcept
Name a dimension of an input tensor.
Definition: NvInfer.h:517
char const * getDimensionName(int32_t index) const noexcept
Get the name of an input dimension.
Definition: NvInfer.h:532
TRT_DEPRECATED void setLocation(TensorLocation location) noexcept
Set the storage location of a tensor.
Definition: NvInfer.h:364
Dims getDimensions() const noexcept
Get the dimensions of a tensor.
Definition: NvInfer.h:242
TensorFormats getAllowedFormats() const noexcept
Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor,...
Definition: NvInfer.h:439
Class to handle tactic timing info collected from builder.
Definition: NvInfer.h:8477
bool combine(ITimingCache const &inputCache, bool ignoreMismatch) noexcept
Combine input timing cache into local instance.
Definition: NvInfer.h:8514
virtual ~ITimingCache() noexcept=default
apiv::VTimingCache * mImpl
Definition: NvInfer.h:8530
bool reset() noexcept
Empty the timing cache.
Definition: NvInfer.h:8524
Layer that represents a TopK reduction.
Definition: NvInfer.h:3522
void setK(int32_t k) noexcept
Set the static k value for the layer.
Definition: NvInfer.h:3553
void setReduceAxes(uint32_t reduceAxes) noexcept
Set which axes to reduce for the layer.
Definition: NvInfer.h:3577
TopKOperation getOperation() const noexcept
Get the operation for the layer.
Definition: NvInfer.h:3539
apiv::VTopKLayer * mImpl
Definition: NvInfer.h:3609
void setOperation(TopKOperation op) noexcept
Set the operation for the layer.
Definition: NvInfer.h:3529
int32_t getK() const noexcept
Get the k value for the layer.
Definition: NvInfer.h:3567
uint32_t getReduceAxes() const noexcept
Get the axes to reduce for the layer.
Definition: NvInfer.h:3587
virtual ~ITopKLayer() noexcept=default
A layer that represents a trip-count limiter.
Definition: NvInfer.h:4725
TripLimit getTripLimit() const noexcept
Get a trip limiter type.
Definition: NvInfer.h:4730
virtual ~ITripLimitLayer() noexcept=default
Layer that represents an unary operation.
Definition: NvInfer.h:2802
void setOperation(UnaryOperation op) noexcept
Set the unary operation for the layer.
Definition: NvInfer.h:2811
apiv::VUnaryLayer * mImpl
Definition: NvInfer.h:2827
UnaryOperation getOperation() const noexcept
Get the unary operation for the layer.
Definition: NvInfer.h:2821
virtual ~IUnaryLayer() noexcept=default
An Interface class for version control.
Definition: NvInferRuntimeBase.h:260
Version information associated with a TRT interface.
Definition: NvInferRuntimeBase.h:225
An array of weights used as a layer parameter.
Definition: NvInferRuntime.h:124
Definition: NvInfer.h:8154
virtual int32_t selectAlgorithms(IAlgorithmContext const &context, IAlgorithm const *const *choices, int32_t nbChoices, int32_t *selection) noexcept=0
Select Algorithms for a layer from the given list of algorithm choices.
virtual void reportAlgorithms(IAlgorithmContext const *const *algoContexts, IAlgorithm const *const *algoChoices, int32_t nbAlgorithms) noexcept=0
Called by TensorRT to report choices it made.
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:8159
virtual ~IAlgorithmSelector() noexcept=default
Definition: NvInferRuntimeBase.h:397
Definition: NvInferRuntime.h:1532
Definition: NvInfer.h:7789
~IInt8EntropyCalibrator2() noexcept override=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7802
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7794
Definition: NvInfer.h:7749
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7762
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7754
~IInt8EntropyCalibrator() noexcept override=default
Definition: NvInfer.h:7868
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7881
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7873
virtual double getQuantile() const noexcept=0
The quantile (between 0 and 1) that will be used to select the region maximum when the quantile metho...
Definition: NvInfer.h:7829
~IInt8MinMaxCalibrator() noexcept override=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7842
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7834
Definition: NvInferPluginBase.h:199
Definition: NvInfer.h:8689
virtual bool stepComplete(char const *phaseName, int32_t step) noexcept=0
Signal that a step of an optimizer phase has finished.
virtual ~IProgressMonitor() noexcept=default
IProgressMonitor()=default
virtual void phaseFinish(char const *phaseName) noexcept=0
Signal that a phase of the optimizer has finished.
virtual void phaseStart(char const *phaseName, char const *parentPhase, int32_t nbSteps) noexcept=0
Signal that a phase of the optimizer has started.
IBuilder * createInferBuilder(ILogger &logger) noexcept
Create an instance of an IBuilder class.
Definition: NvInfer.h:9979
The TensorRT API version 1 namespace.
uint32_t TacticSources
Represents a collection of one or more TacticSource values combine using bitwise-OR operations.
Definition: NvInferRuntime.h:2733
ResizeSelector
The coordinate selector when resize to single pixel output.
Definition: NvInfer.h:3997
@ kFORMULA
Use formula to map the original index.
@ kUPPER
Select the upper left pixel.
EngineCapability
List of supported engine capability flows.
Definition: NvInferRuntime.h:76
nvinfer1::IPluginRegistry * getBuilderPluginRegistry(nvinfer1::EngineCapability capability) noexcept
Return the plugin registry for building a Standard engine, or nullptr if no registry exists.
MemoryPoolType
The type for memory pools used by TensorRT.
Definition: NvInfer.h:8541
ScaleMode
Controls how shift, scale and power are applied in a Scale layer.
Definition: NvInfer.h:1810
@ kUNIFORM
Identical coefficients across all elements of the tensor.
@ kCHANNEL
Per-channel coefficients.
RuntimePlatform
Describes the intended runtime platform (operating system and CPU architecture) for the execution of ...
Definition: NvInfer.h:8263
uint32_t QuantizationFlags
Represents one or more QuantizationFlag values using binary OR operations.
Definition: NvInfer.h:8215
HardwareCompatibilityLevel
Describes requirements of compatibility with GPU architectures other than that of the GPU on which th...
Definition: NvInfer.h:8655
BoundingBoxFormat
Representation of bounding box data used for the Boxes input tensor in INMSLayer.
Definition: NvInfer.h:5920
@ kCENTER_SIZES
(x_center, y_center, width, height) where (x_center, y_center) is the center point of the box
@ kCORNER_PAIRS
(x1, y1, x2, y2) where (x1, y1) and (x2, y2) are any pair of diagonal corners
constexpr int32_t EnumMax< BuilderFlag >() noexcept
Definition: NvInfer.h:8458
constexpr int32_t EnumMax< LayerType >() noexcept
Definition: NvInfer.h:114
constexpr int32_t EnumMax< CalibrationAlgoType >() noexcept
Definition: NvInfer.h:7664
UnaryOperation
Enumerates the unary operations that may be performed by a Unary layer.
Definition: NvInfer.h:2755
@ kISINF
Return true if input value equals +/- infinity for floating-point data type.
@ kCOSH
Hyperbolic cosine.
@ kACOSH
Inverse hyperbolic cosine.
@ kERF
Gauss error function.
@ kISNAN
Return true if input value is a NaN for floating-point data type.
@ kROUND
Round to nearest even for floating-point data type.
@ kATANH
Inverse hyperbolic tangent.
@ kASINH
Inverse hyperbolic sine.
@ kSIGN
Sign, If input > 0, output 1; if input < 0, output -1; if input == 0, output 0.
constexpr int32_t EnumMax< ReduceOperation >() noexcept
Definition: NvInfer.h:2864
constexpr int32_t EnumMax< TripLimit >() noexcept
Definition: NvInfer.h:4394
ActivationType
Enumerates the types of activation to perform in an activation layer.
Definition: NvInfer.h:133
@ kSELU
Selu activation: x>0 ? beta * x : beta * (alpha*exp(x) - alpha)
@ kSCALED_TANH
Scaled tanh activation: alpha*tanh(beta*x)
@ kRELU
Rectified linear activation.
@ kELU
Elu activation: x>=0 ? x : alpha * (exp(x) - 1).
@ kLEAKY_RELU
LeakyRelu activation: x>=0 ? x : alpha * x.
@ kSOFTSIGN
Softsign activation: x / (1+|x|)
@ kHARD_SIGMOID
Hard sigmoid activation: max(0, min(1, alpha*x+beta))
@ kTHRESHOLDED_RELU
Thresholded ReLU activation: x>alpha ? x : 0.
@ kSIGMOID
Sigmoid activation.
@ kCLIP
Clip activation: max(alpha, min(beta, x))
@ kGELU_TANH
GELU tanh activation: 0.5 * x * (1 + tanh(sqrt(2/pi) * (0.044715F * pow(x, 3) + x)))
@ kGELU_ERF
GELU erf activation: 0.5 * x * (1 + erf(sqrt(0.5) * x))
@ kSOFTPLUS
Parametric softplus activation: alpha*log(exp(beta*x)+1)
FillOperation
Enumerates the tensor fill operations that may performed by a fill layer.
Definition: NvInfer.h:4972
@ kRANDOM_UNIFORM
Randomly draw values from a uniform distribution.
@ kRANDOM_NORMAL
Randomly draw values from a normal distribution.
ResizeRoundMode
The rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4027
@ kHALF_DOWN
Round half down.
nvinfer1::safe::IPluginRegistry * getBuilderSafePluginRegistry(nvinfer1::EngineCapability capability) noexcept
Return the plugin registry for building a Safety engine, or nullptr if no registry exists.
PaddingMode
Enumerates the modes of padding to perform in convolution, deconvolution and pooling layer,...
Definition: NvInfer.h:988
@ kSAME_LOWER
Use SAME padding, with prePadding >= postPadding.
@ kEXPLICIT_ROUND_DOWN
Use explicit padding, rounding output size down.
@ kEXPLICIT_ROUND_UP
Use explicit padding, rounding output size up.
@ kSAME_UPPER
Use SAME padding, with prePadding <= postPadding.
TripLimit
Definition: NvInfer.h:4382
@ kWHILE
Tensor is a scalar of type kBOOL. Loop terminates when value is false.
@ kCOUNT
Tensor is a scalar of type kINT32 or kINT64 that contains the trip count.
uint32_t NetworkDefinitionCreationFlags
Represents one or more NetworkDefinitionCreationFlag flags using binary OR operations....
Definition: NvInfer.h:9641
PreviewFeature
Define preview features.
Definition: NvInfer.h:8616
@ kALIASED_PLUGIN_IO_10_03
constexpr int32_t EnumMax< GatherMode >() noexcept
Definition: NvInfer.h:2516
DataType
The type of weights and tensors.
Definition: NvInferRuntimeBase.h:133
uint32_t BuilderFlags
Represents one or more BuilderFlag values using binary OR operations, e.g., 1U << BuilderFlag::kFP16 ...
Definition: NvInfer.h:8293
DeviceType
The device that this layer/network will execute on.
Definition: NvInferRuntime.h:1227
constexpr int32_t EnumMax< ScaleMode >() noexcept
Definition: NvInfer.h:1822
CalibrationAlgoType
Version of calibration algorithm to use.
Definition: NvInfer.h:7651
@ kENTROPY_CALIBRATION_2
Entropy calibration.
@ kLEGACY_CALIBRATION
Legacy calibration.
@ kENTROPY_CALIBRATION
Legacy entropy calibration.
@ kMINMAX_CALIBRATION
Minmax calibration.
LayerType
The type values of layer classes.
Definition: NvInfer.h:58
@ kGRID_SAMPLE
Grid sample layer.
@ kRAGGED_SOFTMAX
Ragged softmax layer.
@ kDECONVOLUTION
Deconvolution layer.
@ kASSERTION
Assertion layer.
@ kMATRIX_MULTIPLY
Matrix multiply layer.
@ kCONDITION
Condition layer.
@ kCONDITIONAL_INPUT
Conditional Input layer.
@ kIDENTITY
Identity layer.
@ kNORMALIZATION
Normalization layer.
@ kQUANTIZE
Quantize layer.
@ kCONVOLUTION
Convolution layer.
@ kPARAMETRIC_RELU
Parametric ReLU layer.
@ kCONCATENATION
Concatenation layer.
@ kREVERSE_SEQUENCE
Reverse sequence layer.
@ kRECURRENCE
Loop Recurrence layer.
@ kDEQUANTIZE
Dequantize layer.
@ kPLUGIN_V3
PluginV3 layer.
@ kITERATOR
Loop Iterator layer.
@ kTRIP_LIMIT
Loop Trip limit layer.
@ kUNARY
UnaryOp operation Layer.
@ kACTIVATION
Activation layer.
@ kELEMENTWISE
Elementwise layer.
@ kPLUGIN_V2
PluginV2 layer.
@ kLOOP_OUTPUT
Loop output layer.
@ kCONDITIONAL_OUTPUT
Conditional Output layer.
@ kCONSTANT
Constant layer.
@ kNON_ZERO
NonZero layer.
constexpr int32_t EnumMax< QuantizationFlag >() noexcept
Definition: NvInfer.h:8240
SampleMode
Controls how ISliceLayer and IGridSample handle out-of-bounds coordinates.
Definition: NvInfer.h:3213
@ kCLAMP
Out of bounds indices are clamped to bounds.
@ kSTRICT_BOUNDS
Fail with error when the coordinates are out of bounds.
@ kWRAP
Coordinates wrap around periodically.
GatherMode
Control form of IGatherLayer.
Definition: NvInfer.h:2504
@ kDEFAULT
Similar to ONNX Gather.
@ kELEMENT
Similar to ONNX GatherElements.
@ kND
Similar to ONNX GatherND.
uint32_t TensorFormats
It is capable of representing one or more TensorFormat by binary OR operations, e....
Definition: NvInfer.h:125
ProfilingVerbosity
List of verbosity levels of layer information exposed in NVTX annotations and in IEngineInspector.
Definition: NvInferRuntime.h:2745
NetworkDefinitionCreationFlag
List of immutable network properties expressed at network creation time. NetworkDefinitionCreationFla...
Definition: NvInfer.h:9652
ElementWiseOperation
Enumerates the binary operations that may be performed by an ElementWise layer.
Definition: NvInfer.h:2414
@ kSUB
Subtract the second element from the first.
@ kSUM
Sum of the two elements.
@ kPROD
Product of the two elements.