154 static constexpr int32_t kVALUE = 12;
193 mImpl->setName(name);
205 return mImpl->getName();
224 mImpl->setDimensions(dimensions);
237 return mImpl->getDimensions();
252 mImpl->setType(type);
264 return mImpl->getType();
279 return mImpl->setDynamicRange(min, max);
287 return mImpl->isNetworkInput();
295 return mImpl->isNetworkOutput();
317 mImpl->setBroadcastAcrossBatch(broadcastAcrossBatch);
333 return mImpl->getBroadcastAcrossBatch();
343 return mImpl->getLocation();
358 mImpl->setLocation(location);
368 return mImpl->dynamicRangeIsSet();
376 mImpl->resetDynamicRange();
386 return mImpl->getDynamicRangeMin();
396 return mImpl->getDynamicRangeMax();
415 mImpl->setAllowedFormats(formats);
428 return mImpl->getAllowedFormats();
463 return mImpl->isShapeTensor();
486 return mImpl->isExecutionTensor();
512 mImpl->setDimensionName(index, name);
527 return mImpl->getDimensionName(index);
552 return mLayer->getType();
566 mLayer->setName(name);
576 return mLayer->getName();
584 return mLayer->getNbInputs();
597 return mLayer->getInput(index);
605 return mLayer->getNbOutputs();
616 return mLayer->getOutput(index);
633 return mLayer->setInput(index, tensor);
661 mLayer->setPrecision(dataType);
673 return mLayer->getPrecision();
685 return mLayer->precisionIsSet();
695 mLayer->resetPrecision();
733 mLayer->setOutputType(index, dataType);
747 return mLayer->getOutputType(index);
760 return mLayer->outputTypeIsSet(index);
772 return mLayer->resetOutputType(index);
790 mLayer->setMetadata(metadata);
803 return mLayer->getMetadata();
808 apiv::VLayer* mLayer;
1053 static constexpr int32_t kVALUE = 6;
1083 mImpl->setKernelSize(kernelSize);
1095 return mImpl->getKernelSize();
1107 mImpl->setNbOutputMaps(nbOutputMaps);
1117 return mImpl->getNbOutputMaps();
1133 mImpl->setStride(stride);
1143 return mImpl->getStride();
1163 return mImpl->setPadding(padding);
1175 return mImpl->getPadding();
1195 mImpl->setNbGroups(nbGroups);
1205 return mImpl->getNbGroups();
1219 mImpl->setKernelWeights(weights);
1229 return mImpl->getKernelWeights();
1244 mImpl->setBiasWeights(weights);
1254 return mImpl->getBiasWeights();
1270 return mImpl->setDilation(dilation);
1282 return mImpl->getDilation();
1299 mImpl->setPrePadding(padding);
1309 return mImpl->getPrePadding();
1326 mImpl->setPostPadding(padding);
1336 return mImpl->getPostPadding();
1350 mImpl->setPaddingMode(paddingMode);
1362 return mImpl->getPaddingMode();
1375 mImpl->setKernelSizeNd(kernelSize);
1385 return mImpl->getKernelSizeNd();
1400 mImpl->setStrideNd(stride);
1410 return mImpl->getStrideNd();
1428 mImpl->setPaddingNd(padding);
1440 return mImpl->getPaddingNd();
1454 mImpl->setDilationNd(dilation);
1464 return mImpl->getDilationNd();
1530 mImpl->setNbOutputChannels(nbOutputs);
1540 return mImpl->getNbOutputChannels();
1550 mImpl->setKernelWeights(weights);
1560 return mImpl->getKernelWeights();
1572 mImpl->setBiasWeights(weights);
1582 return mImpl->getBiasWeights();
1638 mImpl->setActivationType(type);
1648 return mImpl->getActivationType();
1663 mImpl->setAlpha(alpha);
1677 mImpl->setBeta(beta);
1686 return mImpl->getAlpha();
1695 return mImpl->getBeta();
1725 static constexpr int32_t kVALUE = 3;
1752 mImpl->setPoolingType(type);
1762 return mImpl->getPoolingType();
1776 mImpl->setWindowSize(windowSize);
1788 return mImpl->getWindowSize();
1804 mImpl->setStride(stride);
1816 return mImpl->getStride();
1832 mImpl->setPadding(padding);
1846 return mImpl->getPadding();
1861 mImpl->setBlendFactor(blendFactor);
1874 return mImpl->getBlendFactor();
1891 mImpl->setAverageCountExcludesPadding(exclusive);
1902 return mImpl->getAverageCountExcludesPadding();
1920 mImpl->setPrePadding(padding);
1930 return mImpl->getPrePadding();
1948 mImpl->setPostPadding(padding);
1958 return mImpl->getPostPadding();
1971 mImpl->setPaddingMode(paddingMode);
1982 return mImpl->getPaddingMode();
1995 mImpl->setWindowSizeNd(windowSize);
2005 return mImpl->getWindowSizeNd();
2020 mImpl->setStrideNd(stride);
2030 return mImpl->getStrideNd();
2049 mImpl->setPaddingNd(padding);
2061 return mImpl->getPaddingNd();
2092 mImpl->setWindowSize(windowSize);
2102 return mImpl->getWindowSize();
2113 mImpl->setAlpha(alpha);
2123 return mImpl->getAlpha();
2134 mImpl->setBeta(beta);
2144 return mImpl->getBeta();
2165 return mImpl->getK();
2232 mImpl->setMode(mode);
2242 return mImpl->getMode();
2252 mImpl->setShift(shift);
2262 return mImpl->getShift();
2272 mImpl->setScale(scale);
2282 return mImpl->getScale();
2292 mImpl->setPower(power);
2302 return mImpl->getPower();
2317 return mImpl->getChannelAxis();
2338 mImpl->setChannelAxis(channelAxis);
2402 mImpl->setAxes(axes);
2412 return mImpl->getAxes();
2449 mImpl->setAxis(axis);
2459 return mImpl->getAxis();
2490 mImpl->setKernelSize(kernelSize);
2502 return mImpl->getKernelSize();
2514 mImpl->setNbOutputMaps(nbOutputMaps);
2524 return mImpl->getNbOutputMaps();
2540 mImpl->setStride(stride);
2552 return mImpl->getStride();
2572 mImpl->setPadding(padding);
2586 return mImpl->getPadding();
2606 mImpl->setNbGroups(nbGroups);
2616 return mImpl->getNbGroups();
2630 mImpl->setKernelWeights(weights);
2640 return mImpl->getKernelWeights();
2655 mImpl->setBiasWeights(weights);
2665 return mImpl->getBiasWeights();
2683 mImpl->setPrePadding(padding);
2693 return mImpl->getPrePadding();
2711 mImpl->setPostPadding(padding);
2721 return mImpl->getPostPadding();
2735 mImpl->setPaddingMode(paddingMode);
2747 return mImpl->getPaddingMode();
2762 mImpl->setKernelSizeNd(kernelSize);
2772 return mImpl->getKernelSizeNd();
2789 mImpl->setStrideNd(stride);
2799 return mImpl->getStrideNd();
2817 mImpl->setPaddingNd(padding);
2829 return mImpl->getPaddingNd();
2853 mImpl->setDilationNd(dilation);
2863 return mImpl->getDilationNd();
2912 static constexpr int32_t kVALUE = 14;
2949 return mImpl->setOperation(op);
2961 return mImpl->getOperation();
3084 mImpl->setGatherAxis(axis);
3095 return mImpl->getGatherAxis();
3116 mImpl->setNbElementWiseDims(elementWiseDims);
3126 return mImpl->getNbElementWiseDims();
3136 mImpl->setMode(mode);
3146 return mImpl->getMode();
3354 return mImpl->getLayerCount();
3358 return mImpl->getHiddenSize();
3362 return mImpl->getMaxSeqLength();
3366 return mImpl->getDataLength();
3385 return mImpl->setSequenceLengths(seqLengths);
3397 return mImpl->getSequenceLengths();
3407 mImpl->setOperation(op);
3417 return mImpl->getOperation();
3427 mImpl->setInputMode(op);
3437 return mImpl->getInputMode();
3452 mImpl->setDirection(op);
3462 return mImpl->getDirection();
3520 mImpl->setWeightsForGate(layerIndex, gate, isW, weights);
3530 return mImpl->getWeightsForGate(layerIndex, gate, isW);
3554 mImpl->setBiasForGate(layerIndex, gate, isW, bias);
3564 return mImpl->getBiasForGate(layerIndex, gate, isW);
3582 mImpl->setHiddenState(hidden);
3592 return mImpl->getHiddenState();
3612 mImpl->setCellState(cell);
3622 return mImpl->getCellState();
3649 return mImpl->getPlugin();
3732 mImpl->setOperation(op);
3742 return mImpl->getOperation();
3805 mImpl->setOperation(op);
3815 return mImpl->getOperation();
3825 mImpl->setReduceAxes(reduceAxes);
3835 return mImpl->getReduceAxes();
3845 mImpl->setKeepDimensions(keepDimensions);
3855 return mImpl->getKeepDimensions();
3887 mImpl->setPrePadding(padding);
3899 return mImpl->getPrePadding();
3913 mImpl->setPostPadding(padding);
3925 return mImpl->getPostPadding();
3939 mImpl->setPrePaddingNd(padding);
3951 return mImpl->getPrePaddingNd();
3965 mImpl->setPostPaddingNd(padding);
3977 return mImpl->getPostPaddingNd();
4022 mImpl->setFirstTranspose(permutation);
4034 return mImpl->getFirstTranspose();
4059 mImpl->setReshapeDimensions(dimensions);
4072 return mImpl->getReshapeDimensions();
4119 mImpl->setSecondTranspose(permutation);
4131 return mImpl->getSecondTranspose();
4147 return mImpl->setZeroIsPlaceholder(zeroIsPlaceholder);
4160 return mImpl->getZeroIsPlaceholder();
4255 mImpl->setStart(start);
4270 return mImpl->getStart();
4284 return mImpl->setSize(size);
4299 return mImpl->getSize();
4313 mImpl->setStride(stride);
4328 return mImpl->getStride();
4338 mImpl->setMode(mode);
4348 return mImpl->getMode();
4443 mImpl->setOperation(op);
4453 return mImpl->getOperation();
4481 return mImpl->getK();
4491 mImpl->setReduceAxes(reduceAxes);
4501 return mImpl->getReduceAxes();
4601 mImpl->setOperation(index, op);
4613 return mImpl->getOperation(index);
4718 mImpl->setToType(toType);
4726 return mImpl->getToType();
4756 mImpl->setWeights(weights);
4766 return mImpl->getWeights();
4778 mImpl->setDimensions(dimensions);
4790 return mImpl->getDimensions();
4839 static constexpr int32_t kVALUE = 3;
4893 static constexpr int32_t kVALUE = 3;
4923 static constexpr int32_t kVALUE = 2;
4959 static constexpr int32_t kVALUE = 4;
5022 return mImpl->setOutputDimensions(dimensions);
5032 return mImpl->getOutputDimensions();
5060 void setScales(
float const* scales, int32_t nbScales)
noexcept
5062 mImpl->setScales(scales, nbScales);
5079 int32_t
getScales(int32_t size,
float* scales)
const noexcept
5081 return mImpl->getScales(size, scales);
5093 mImpl->setResizeMode(resizeMode);
5103 return mImpl->getResizeMode();
5119 mImpl->setAlignCorners(alignCorners);
5131 return mImpl->getAlignCorners();
5166 mImpl->setCoordinateTransformation(coordTransform);
5176 return mImpl->getCoordinateTransformation();
5191 mImpl->setSelectorForSinglePixel(selector);
5201 return mImpl->getSelectorForSinglePixel();
5215 mImpl->setNearestRounding(value);
5225 return mImpl->getNearestRounding();
5247 mImpl->setCubicCoeff(A);
5257 return mImpl->getCubicCoeff();
5270 mImpl->setExcludeOutside(excludeFlag);
5280 return mImpl->getExcludeOutside();
5339 return mBoundary->getLoop();
5344 apiv::VLoopBoundaryLayer* mBoundary;
5358 return mBoundary->getConditional();
5363 apiv::VConditionalBoundaryLayer* mBoundary;
5436 return mImpl->setCondition(condition);
5452 return mImpl->addOutput(trueSubgraphOutput, falseSubgraphOutput);
5464 return mImpl->addInput(input);
5479 mImpl->setName(name);
5489 return mImpl->getName();
5548 return mImpl->getLoopOutput();
5565 mImpl->setAxis(axis);
5571 return mImpl->getAxis();
5606 return mImpl->getTripLimit();
5620 mImpl->setAxis(axis);
5626 return mImpl->getAxis();
5636 mImpl->setReverse(reverse);
5642 return mImpl->getReverse();
5666 return mImpl->addRecurrence(initialValue);
5687 return mImpl->addTripLimit(tensor, limit);
5700 return mImpl->addIterator(tensor, axis, reverse);
5712 return mImpl->addLoopOutput(tensor, outputKind, axis);
5727 mImpl->setName(name);
5737 return mImpl->getName();
5782 mImpl->setMessage(message);
5792 return mImpl->getMessage();
5865 mImpl->setDimensions(dimensions);
5880 return mImpl->getDimensions();
5890 mImpl->setOperation(op);
5900 return mImpl->getOperation();
5919 mImpl->setAlpha(alpha);
5934 return mImpl->getAlpha();
5953 mImpl->setBeta(beta);
5968 return mImpl->getBeta();
6080 return mImpl->getAxis();
6091 mImpl->setAxis(axis);
6166 return mImpl->getAxis();
6177 mImpl->setAxis(axis);
6234 return mImpl->setEquation(equation);
6244 return mImpl->getEquation();
6340 mImpl->setMode(mode);
6350 return mImpl->getMode();
6360 mImpl->setAxis(axis);
6368 return mImpl->getAxis();
6413 mImpl->setAxis(axis);
6421 return mImpl->getAxis();
6448 mImpl->setInterpolationMode(mode);
6460 return mImpl->getInterpolationMode();
6470 mImpl->setAlignCorners(alignCorners);
6482 return mImpl->getAlignCorners();
6494 return mImpl->setSampleMode(mode);
6506 return mImpl->getSampleMode();
6595 mImpl->setBoundingBoxFormat(fmt);
6607 return mImpl->getBoundingBoxFormat();
6621 mImpl->setTopKBoxLimit(limit);
6631 return mImpl->getTopKBoxLimit();
6683 mImpl->setBatchAxis(batchAxis);
6693 return mImpl->getBatchAxis();
6706 mImpl->setSequenceAxis(sequenceAxis);
6716 return mImpl->getSequenceAxis();
6752 return mImpl->setEpsilon(eps);
6761 return mImpl->getEpsilon();
6770 return mImpl->setAxes(axesMask);
6779 return mImpl->getAxes();
6799 return mImpl->setNbGroups(nbGroups);
6808 return mImpl->getNbGroups();
6826 return mImpl->setComputePrecision(type);
6835 return mImpl->getComputePrecision();
6906 return mImpl->addInput(name, type, dimensions);
6920 mImpl->markOutput(tensor);
6944 return mImpl->addConvolution(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
6967 return mImpl->addFullyConnected(input, nbOutputs, kernelWeights, biasWeights);
6986 return mImpl->addActivation(input, type);
7005 return mImpl->addPooling(input, type, windowSize);
7024 return mImpl->addLRN(input, window, alpha, beta, k);
7051 return mImpl->addScale(input, mode, shift, scale, power);
7064 return mImpl->addSoftMax(input);
7081 return mImpl->addConcatenation(inputs, nbInputs);
7105 return mImpl->addDeconvolution(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7132 return mImpl->addElementWise(input1, input2, op);
7154 return mImpl->addUnary(input, operation);
7171 return mImpl->addPadding(input, prePadding, postPadding);
7185 return mImpl->addShuffle(input);
7202 return mImpl->addOneHot(indices, values, depth, axis);
7214 return mImpl->getNbLayers();
7228 return mImpl->getLayer(index);
7240 return mImpl->getNbInputs();
7256 return mImpl->getInput(index);
7270 return mImpl->getNbOutputs();
7286 return mImpl->getOutput(index);
7326 return mImpl->addReduce(input, operation, reduceAxes, keepDimensions);
7360 return mImpl->addTopK(input, op, k, reduceAxes);
7376 return mImpl->addGather(data, indices, axis);
7392 return mImpl->addGatherV2(data, indices, mode);
7410 return mImpl->addRaggedSoftMax(input, bounds);
7432 return mImpl->addMatrixMultiply(input0, op0, input1, op1);
7446 return mImpl->addNonZero(input);
7473 return mImpl->addConstant(dimensions, weights);
7542 ITensor& input, int32_t layerCount, int32_t hiddenSize, int32_t maxSeqLen,
RNNOperation op)
noexcept
7544 return mImpl->addRNNv2(input, layerCount, hiddenSize, maxSeqLen, op);
7558 return mImpl->addIdentity(input);
7573 return mImpl->addCast(input, toType);
7588 mImpl->removeTensor(tensor);
7600 mImpl->unmarkOutput(tensor);
7619 return mImpl->addPluginV2(inputs, nbInputs, plugin);
7638 return mImpl->addSlice(input, start, size, stride);
7662 mImpl->setName(name);
7676 return mImpl->getName();
7692 return mImpl->addShape(input);
7710 return mImpl->hasImplicitBatchDimension();
7728 return mImpl->markOutputForShapes(tensor);
7740 return mImpl->unmarkOutputForShapes(tensor);
7758 return mImpl->addParametricReLU(input, slope);
7781 return mImpl->addConvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7800 return mImpl->addPoolingNd(input, type, windowSize);
7823 return mImpl->addDeconvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7860 return mImpl->addScaleNd(input, mode, shift, scale, power, channelAxis);
7875 return mImpl->addResize(input);
7889 return mImpl->hasExplicitPrecision();
7905 return mImpl->addLoop();
7945 return mImpl->addSelect(condition, thenInput, elseInput);
7962 return mImpl->addAssertion(condition, message);
7985 return mImpl->addFill(dimensions, op);
8002 return mImpl->addPaddingNd(input, prePadding, postPadding);
8025 return mImpl->setWeightsName(weights, name);
8044 mImpl->setErrorRecorder(recorder);
8059 return mImpl->getErrorRecorder();
8078 return mImpl->addDequantize(input, scale);
8098 return mImpl->addScatter(data, indices, updates, mode);
8117 return mImpl->addQuantize(input, scale);
8132 return mImpl->addIfConditional();
8146 return mImpl->addEinsum(inputs, nbInputs, equation);
8162 return mImpl->addGridSample(input, grid);
8180 return mImpl->addNMS(boxes, scores, maxOutputBoxesPerClass);
8197 return mImpl->addReverseSequence(input, sequenceLens);
8224 return mImpl->addNormalization(input, scale, bias, axesMask);
8235 return mImpl->getBuilder();
8300 virtual
bool getBatch(
void* bindings[],
char const* names[], int32_t nbBindings) noexcept = 0;
8316 virtual
void const* readCalibrationCache(std::
size_t& length) noexcept = 0;
8326 virtual
void writeCalibrationCache(
void const* ptr, std::
size_t length) noexcept = 0;
8420 virtual
double getRegressionCutoff() const noexcept = 0;
8434 virtual
void const* readHistogramCache(std::
size_t& length) noexcept = 0;
8444 virtual
void writeHistogramCache(
void const* ptr, std::
size_t length) noexcept = 0;
8472 return mImpl->getTensorFormat();
8482 return mImpl->getDataType();
8493 return mImpl->getStrides();
8503 return mImpl->getVectorizedDim();
8514 return mImpl->getComponentsPerElement();
8541 return mImpl->getImplementation();
8549 return mImpl->getTactic();
8574 return mImpl->getName();
8585 return mImpl->getDimensions(index, select);
8593 return mImpl->getNbInputs();
8601 return mImpl->getNbOutputs();
8633 return mImpl->getAlgorithmIOInfo(index);
8641 return mImpl->getAlgorithmVariant();
8649 return mImpl->getTimingMSec();
8657 return mImpl->getWorkspaceSize();
8670 return mImpl->getAlgorithmIOInfoByIndex(index);
8704 int32_t nbChoices, int32_t* selection)
noexcept = 0;
8716 int32_t nbAlgorithms)
noexcept = 0;
8892 return mImpl->serialize();
8916 return mImpl->combine(inputCache, ignoreMismatch);
8926 return mImpl->reset();
9049 static constexpr int32_t kVALUE = 3;
9079 static constexpr int32_t kVALUE = 2;
9109 mImpl->setMinTimingIterations(minTiming);
9123 return mImpl->getMinTimingIterations();
9136 mImpl->setAvgTimingIterations(avgTiming);
9148 return mImpl->getAvgTimingIterations();
9161 mImpl->setEngineCapability(capability);
9173 return mImpl->getEngineCapability();
9183 mImpl->setInt8Calibrator(calibrator);
9191 return mImpl->getInt8Calibrator();
9206 mImpl->setMaxWorkspaceSize(workspaceSize);
9223 return mImpl->getMaxWorkspaceSize();
9240 mImpl->setFlags(builderFlags);
9252 return mImpl->getFlags();
9264 mImpl->clearFlag(builderFlag);
9276 mImpl->setFlag(builderFlag);
9288 return mImpl->getFlag(builderFlag);
9304 mImpl->setDeviceType(layer, deviceType);
9313 return mImpl->getDeviceType(layer);
9323 return mImpl->isDeviceTypeSet(layer);
9333 mImpl->resetDeviceType(layer);
9342 return mImpl->canRunOnDLA(layer);
9357 mImpl->setDLACore(dlaCore);
9366 return mImpl->getDLACore();
9376 mImpl->setDefaultDeviceType(deviceType);
9386 return mImpl->getDefaultDeviceType();
9422 return mImpl->setProfileStream(stream);
9434 return mImpl->getProfileStream();
9450 return mImpl->addOptimizationProfile(profile);
9463 return mImpl->getNbOptimizationProfiles();
9475 mImpl->setProfilingVerbosity(verbosity);
9488 return mImpl->getProfilingVerbosity();
9497 mImpl->setAlgorithmSelector(selector);
9505 return mImpl->getAlgorithmSelector();
9520 return mImpl->setCalibrationProfile(profile);
9530 return mImpl->getCalibrationProfile();
9547 mImpl->setQuantizationFlags(flags);
9559 return mImpl->getQuantizationFlags();
9571 mImpl->clearQuantizationFlag(flag);
9583 mImpl->setQuantizationFlag(flag);
9595 return mImpl->getQuantizationFlag(flag);
9617 return mImpl->setTacticSources(tacticSources);
9632 return mImpl->getTacticSources();
9651 return mImpl->createTimingCache(blob, size);
9674 return mImpl->setTimingCache(cache, ignoreMismatch);
9684 return mImpl->getTimingCache();
9716 mImpl->setMemoryPoolLimit(pool, poolSize);
9735 return mImpl->getMemoryPoolLimit(pool);
9753 mImpl->setPreviewFeature(feature, enable);
9767 return mImpl->getPreviewFeature(feature);
9787 mImpl->setBuilderOptimizationLevel(level);
9799 return mImpl->getBuilderOptimizationLevel();
9815 mImpl->setHardwareCompatibilityLevel(hardwareCompatibilityLevel);
9828 return mImpl->getHardwareCompatibilityLevel();
9841 mImpl->setPluginsToSerialize(paths, nbPaths);
9854 return mImpl->getPluginToSerialize(index);
9864 return mImpl->getNbPluginsToSerialize();
9893 mImpl->setMaxAuxStreams(nbStreams);
9903 return mImpl->getMaxAuxStreams();
9975 mImpl->setMaxBatchSize(batchSize);
9990 return mImpl->getMaxBatchSize();
9998 return mImpl->platformHasFastFp16();
10006 return mImpl->platformHasFastInt8();
10030 return mImpl->getMaxDLABatchSize();
10038 return mImpl->getNbDLACores();
10054 mImpl->setGpuAllocator(allocator);
10064 return mImpl->createBuilderConfig();
10080 return mImpl->buildEngineWithConfig(network, config);
10097 return mImpl->createNetworkV2(flags);
10111 return mImpl->createOptimizationProfile();
10130 mImpl->setErrorRecorder(recorder);
10145 return mImpl->getErrorRecorder();
10161 return mImpl->platformHasTf32();
10180 return mImpl->buildSerializedNetwork(network, config);
10204 return mImpl->isNetworkSupported(network, config);
10214 return mImpl->getLogger();
10228 return mImpl->setMaxThreads(maxThreads);
10242 return mImpl->getMaxThreads();
10252 return mImpl->getPluginRegistry();
10265extern "C" TENSORRTAPI void* createInferBuilder_INTERNAL(
void* logger, int32_t version)
noexcept;
10279inline IBuilder* createInferBuilder(ILogger& logger)
noexcept
10281 return static_cast<IBuilder*
>(createInferBuilder_INTERNAL(&logger,
NV_TENSORRT_VERSION));
#define TENSORRTAPI
Definition: NvInferRuntimeBase.h:54
#define NV_TENSORRT_VERSION
Definition: NvInferRuntimeBase.h:76
#define TRT_DEPRECATED
Definition: NvInferRuntimeBase.h:40
#define TRT_DEPRECATED_ENUM
Definition: NvInferRuntimeBase.h:41
Definition: NvInferRuntimeBase.h:179
static constexpr int32_t MAX_DIMS
The maximum rank (number of dimensions) supported for a tensor.
Definition: NvInferRuntimeBase.h:182
Descriptor for two-dimensional spatial data.
Definition: NvInferLegacyDims.h:70
An Activation layer in a network definition.
Definition: NvInfer.h:1627
void setBeta(float beta) noexcept
Set the beta parameter (must be finite).
Definition: NvInfer.h:1675
void setActivationType(ActivationType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1636
ActivationType getActivationType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1646
float getAlpha() const noexcept
Get the alpha parameter.
Definition: NvInfer.h:1684
virtual ~IActivationLayer() noexcept=default
float getBeta() const noexcept
Get the beta parameter.
Definition: NvInfer.h:1693
void setAlpha(float alpha) noexcept
Set the alpha parameter (must be finite).
Definition: NvInfer.h:1661
Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorith...
Definition: NvInfer.h:8566
int32_t getNbOutputs() const noexcept
Return number of outputs of the algorithm.
Definition: NvInfer.h:8599
int32_t getNbInputs() const noexcept
Return number of inputs of the algorithm.
Definition: NvInfer.h:8591
char const * getName() const noexcept
Return name of the algorithm node. This is a unique identifier for the IAlgorithmContext.
Definition: NvInfer.h:8572
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:8583
Describes a variation of execution of a layer. An algorithm is represented by IAlgorithmVariant and t...
Definition: NvInfer.h:8619
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:8655
float getTimingMSec() const noexcept
The time in milliseconds to execute the algorithm.
Definition: NvInfer.h:8647
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:8668
virtual ~IAlgorithm() noexcept=default
TRT_DEPRECATED IAlgorithmIOInfo const & getAlgorithmIOInfo(int32_t index) const noexcept
Returns the format of an Algorithm input or output. Algorithm inputs are incrementally numbered first...
Definition: NvInfer.h:8631
IAlgorithmVariant const & getAlgorithmVariant() const noexcept
Returns the algorithm variant.
Definition: NvInfer.h:8639
Carries information about input or output of the algorithm. IAlgorithmIOInfo for all the input and ou...
Definition: NvInfer.h:8460
virtual ~IAlgorithmIOInfo() noexcept=default
TRT_DEPRECATED TensorFormat getTensorFormat() const noexcept
Return TensorFormat of the input/output of algorithm.
Definition: NvInfer.h:8470
int64_t getVectorizedDim() const noexcept
Return the index of the vectorized dimension or -1 for non-vectorized formats.
Definition: NvInfer.h:8501
Dims getStrides() const noexcept
Return strides of the input/output tensor of algorithm. For vectorized formats, strides are given in ...
Definition: NvInfer.h:8491
DataType getDataType() const noexcept
Return DataType of the input/output of algorithm.
Definition: NvInfer.h:8480
int64_t getComponentsPerElement() const noexcept
Return the number of components per element. This is always 1 for non-vectorized formats.
Definition: NvInfer.h:8512
Interface implemented by application for selecting and reporting algorithms of a layer provided by th...
Definition: NvInfer.h:8687
virtual void reportAlgorithms(IAlgorithmContext const *const *algoContexts, IAlgorithm const *const *algoChoices, int32_t nbAlgorithms) noexcept=0
Called by TensorRT to report choices it made.
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 ~IAlgorithmSelector() noexcept=default
provides a unique 128-bit identifier, which along with the input and output information denotes the v...
Definition: NvInfer.h:8534
virtual ~IAlgorithmVariant() noexcept=default
int64_t getTactic() const noexcept
Return tactic of the algorithm.
Definition: NvInfer.h:8547
int64_t getImplementation() const noexcept
Return implementation of the algorithm.
Definition: NvInfer.h:8539
An assertion layer in a network.
Definition: NvInfer.h:5770
void setMessage(char const *message) noexcept
Set the message to print if the assertion fails.
Definition: NvInfer.h:5780
char const * getMessage() const noexcept
Return the assertion message.
Definition: NvInfer.h:5790
virtual ~IAssertionLayer() noexcept=default
Holds properties for configuring a builder to produce an engine.
Definition: NvInfer.h:9091
virtual TRT_DEPRECATED int32_t getMinTimingIterations() const noexcept
Query the number of minimization iterations.
Definition: NvInfer.h:9121
IOptimizationProfile const * getCalibrationProfile() noexcept
Get the current calibration profile.
Definition: NvInfer.h:9528
void setMemoryPoolLimit(MemoryPoolType pool, std::size_t poolSize) noexcept
Set the memory size for the memory pool.
Definition: NvInfer.h:9714
void setQuantizationFlag(QuantizationFlag flag) noexcept
Set a single quantization flag.
Definition: NvInfer.h:9581
nvinfer1::ITimingCache * createTimingCache(void const *blob, std::size_t size) const noexcept
Create timing cache.
Definition: NvInfer.h:9649
void setPreviewFeature(PreviewFeature feature, bool enable) noexcept
Enable or disable a specific preview feature.
Definition: NvInfer.h:9751
void setInt8Calibrator(IInt8Calibrator *calibrator) noexcept
Set Int8 Calibration interface.
Definition: NvInfer.h:9181
bool getPreviewFeature(PreviewFeature feature) const noexcept
Get status of preview feature.
Definition: NvInfer.h:9765
void clearQuantizationFlag(QuantizationFlag flag) noexcept
clear a quantization flag.
Definition: NvInfer.h:9569
int32_t getBuilderOptimizationLevel() noexcept
Get builder optimization level.
Definition: NvInfer.h:9797
bool setTacticSources(TacticSources tacticSources) noexcept
Set tactic sources.
Definition: NvInfer.h:9615
void setPluginsToSerialize(char const *const *paths, int32_t nbPaths) noexcept
Set the plugin libraries to be serialized with version-compatible engines.
Definition: NvInfer.h:9839
bool getQuantizationFlag(QuantizationFlag flag) const noexcept
Returns true if the quantization flag is set.
Definition: NvInfer.h:9593
std::size_t getMemoryPoolLimit(MemoryPoolType pool) const noexcept
Get the memory size limit of the memory pool.
Definition: NvInfer.h:9733
int32_t getDLACore() const noexcept
Get the DLA core that the engine executes on.
Definition: NvInfer.h:9364
int32_t getNbPluginsToSerialize() const noexcept
Get the number of plugin library paths to be serialized with version-compatible engines.
Definition: NvInfer.h:9862
void setDeviceType(ILayer const *layer, DeviceType deviceType) noexcept
Set the device that this layer must execute on.
Definition: NvInfer.h:9302
void setEngineCapability(EngineCapability capability) noexcept
Configure the builder to target specified EngineCapability flow.
Definition: NvInfer.h:9159
int32_t getMaxAuxStreams() const noexcept
Get the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9901
bool getFlag(BuilderFlag builderFlag) const noexcept
Returns true if the build mode flag is set.
Definition: NvInfer.h:9286
void setQuantizationFlags(QuantizationFlags flags) noexcept
Set the quantization flags.
Definition: NvInfer.h:9545
bool setCalibrationProfile(IOptimizationProfile const *profile) noexcept
Add a calibration profile.
Definition: NvInfer.h:9518
virtual void setAvgTimingIterations(int32_t avgTiming) noexcept
Set the number of averaging iterations used when timing layers.
Definition: NvInfer.h:9134
void setProfilingVerbosity(ProfilingVerbosity verbosity) noexcept
Set verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:9473
IAlgorithmSelector * getAlgorithmSelector() const noexcept
Get Algorithm Selector.
Definition: NvInfer.h:9503
int32_t getNbOptimizationProfiles() const noexcept
Get number of optimization profiles.
Definition: NvInfer.h:9461
QuantizationFlags getQuantizationFlags() const noexcept
Get the quantization flags.
Definition: NvInfer.h:9557
nvinfer1::ITimingCache const * getTimingCache() const noexcept
Get the pointer to the timing cache from current IBuilderConfig.
Definition: NvInfer.h:9682
void reset() noexcept
Resets the builder configuration to defaults.
Definition: NvInfer.h:9394
bool setTimingCache(ITimingCache const &cache, bool ignoreMismatch) noexcept
Attach a timing cache to IBuilderConfig.
Definition: NvInfer.h:9672
TRT_DEPRECATED void destroy() noexcept
Delete this IBuilderConfig.
Definition: NvInfer.h:9408
char const * getPluginToSerialize(int32_t index) const noexcept
Get the plugin library path to be serialized with version-compatible engines.
Definition: NvInfer.h:9852
EngineCapability getEngineCapability() const noexcept
Query EngineCapability flow configured for the builder.
Definition: NvInfer.h:9171
void setAlgorithmSelector(IAlgorithmSelector *selector) noexcept
Set Algorithm Selector.
Definition: NvInfer.h:9495
TRT_DEPRECATED void setMaxWorkspaceSize(std::size_t workspaceSize) noexcept
Set the maximum workspace size.
Definition: NvInfer.h:9204
TRT_DEPRECATED std::size_t getMaxWorkspaceSize() const noexcept
Get the maximum workspace size.
Definition: NvInfer.h:9221
DeviceType getDefaultDeviceType() const noexcept
Get the default DeviceType which was set by setDefaultDeviceType.
Definition: NvInfer.h:9384
BuilderFlags getFlags() const noexcept
Get the build mode flags for this builder config. Defaults to 0.
Definition: NvInfer.h:9250
void setFlags(BuilderFlags builderFlags) noexcept
Set the build mode flags to turn on builder options for this network.
Definition: NvInfer.h:9238
TacticSources getTacticSources() const noexcept
Get tactic sources.
Definition: NvInfer.h:9630
void resetDeviceType(ILayer const *layer) noexcept
reset the DeviceType for this layer
Definition: NvInfer.h:9331
void setDLACore(int32_t dlaCore) noexcept
Sets the DLA core used by the network. Defaults to -1.
Definition: NvInfer.h:9355
HardwareCompatibilityLevel getHardwareCompatibilityLevel() const noexcept
Get the hardware compatibility level.
Definition: NvInfer.h:9826
void clearFlag(BuilderFlag builderFlag) noexcept
clear a single build mode flag.
Definition: NvInfer.h:9262
int32_t addOptimizationProfile(IOptimizationProfile const *profile) noexcept
Add an optimization profile.
Definition: NvInfer.h:9448
apiv::VBuilderConfig * mImpl
Definition: NvInfer.h:9907
int32_t getAvgTimingIterations() const noexcept
Query the number of averaging iterations.
Definition: NvInfer.h:9146
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:9374
void setFlag(BuilderFlag builderFlag) noexcept
Set a single build mode flag.
Definition: NvInfer.h:9274
virtual ~IBuilderConfig() noexcept=default
DeviceType getDeviceType(ILayer const *layer) const noexcept
Get the device that this layer executes on.
Definition: NvInfer.h:9311
bool canRunOnDLA(ILayer const *layer) const noexcept
Checks if a layer can run on DLA.
Definition: NvInfer.h:9340
cudaStream_t getProfileStream() const noexcept
Get the cuda stream that is used to profile this network.
Definition: NvInfer.h:9432
void setHardwareCompatibilityLevel(HardwareCompatibilityLevel hardwareCompatibilityLevel) noexcept
Set the hardware compatibility level.
Definition: NvInfer.h:9813
IInt8Calibrator * getInt8Calibrator() const noexcept
Get Int8 Calibration interface.
Definition: NvInfer.h:9189
void setMaxAuxStreams(int32_t nbStreams) noexcept
Set the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9891
ProfilingVerbosity getProfilingVerbosity() const noexcept
Get verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:9486
bool isDeviceTypeSet(ILayer const *layer) const noexcept
whether the DeviceType has been explicitly set for this layer
Definition: NvInfer.h:9321
void setBuilderOptimizationLevel(int32_t level) noexcept
Set builder optimization level.
Definition: NvInfer.h:9785
void setProfileStream(const cudaStream_t stream) noexcept
Set the cuda stream that is used to profile this network.
Definition: NvInfer.h:9420
Builds an engine from a network definition.
Definition: NvInfer.h:9959
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:10028
int32_t getNbDLACores() const noexcept
Return the number of DLA engines available to this builder.
Definition: NvInfer.h:10036
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:10143
apiv::VBuilder * mImpl
Definition: NvInfer.h:10256
ILogger * getLogger() const noexcept
get the logger with which the builder was created
Definition: NvInfer.h:10212
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:10202
bool platformHasTf32() const noexcept
Determine whether the platform has TF32 support.
Definition: NvInfer.h:10159
int32_t getMaxThreads() const noexcept
get the maximum number of threads that can be used by the builder.
Definition: NvInfer.h:10240
IPluginRegistry & getPluginRegistry() noexcept
get the local plugin registry that can be used by the builder.
Definition: NvInfer.h:10250
TRT_DEPRECATED void destroy() noexcept
Destroy this object.
Definition: NvInfer.h:10016
nvinfer1::IOptimizationProfile * createOptimizationProfile() noexcept
Create a new optimization profile.
Definition: NvInfer.h:10109
bool platformHasFastFp16() const noexcept
Determine whether the platform has fast native fp16.
Definition: NvInfer.h:9996
void setGpuAllocator(IGpuAllocator *allocator) noexcept
Set the GPU allocator.
Definition: NvInfer.h:10052
nvinfer1::INetworkDefinition * createNetworkV2(NetworkDefinitionCreationFlags flags) noexcept
Create a network definition object.
Definition: NvInfer.h:10095
nvinfer1::IBuilderConfig * createBuilderConfig() noexcept
Create a builder configuration object.
Definition: NvInfer.h:10062
void reset() noexcept
Resets the builder state to default values.
Definition: NvInfer.h:10151
bool setMaxThreads(int32_t maxThreads) noexcept
Set the maximum number of threads.
Definition: NvInfer.h:10226
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:10128
bool platformHasFastInt8() const noexcept
Determine whether the platform has fast native int8.
Definition: NvInfer.h:10004
nvinfer1::IHostMemory * buildSerializedNetwork(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds and serializes a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:10178
virtual ~IBuilder() noexcept=default
TRT_DEPRECATED int32_t getMaxBatchSize() const noexcept
Get the maximum batch size.
Definition: NvInfer.h:9988
TRT_DEPRECATED nvinfer1::ICudaEngine * buildEngineWithConfig(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds an engine for the given INetworkDefinition and given IBuilderConfig.
Definition: NvInfer.h:10077
A cast layer in a network.
Definition: NvInfer.h:4711
virtual ~ICastLayer() noexcept=default
apiv::VCastLayer * mImpl
Definition: NvInfer.h:4730
DataType getToType() const noexcept
Return cast layer output type.
Definition: NvInfer.h:4724
void setToType(DataType toType) noexcept
Set cast layer output type.
Definition: NvInfer.h:4716
A concatenation layer in a network definition.
Definition: NvInfer.h:2433
void setAxis(int32_t axis) noexcept
Set the axis along which concatenation occurs.
Definition: NvInfer.h:2447
int32_t getAxis() const noexcept
Get the axis along which concatenation occurs.
Definition: NvInfer.h:2457
virtual ~IConcatenationLayer() noexcept=default
Definition: NvInfer.h:5370
virtual ~IConditionLayer() noexcept=default
Layer that represents a constant value.
Definition: NvInfer.h:4743
void setWeights(Weights weights) noexcept
Set the weights for the layer.
Definition: NvInfer.h:4754
Weights getWeights() const noexcept
Get the weights for the layer.
Definition: NvInfer.h:4764
apiv::VConstantLayer * mImpl
Definition: NvInfer.h:4794
void setDimensions(Dims dimensions) noexcept
Set the dimensions for the layer.
Definition: NvInfer.h:4776
virtual ~IConstantLayer() noexcept=default
Dims getDimensions() const noexcept
Get the dimensions for the layer.
Definition: NvInfer.h:4788
A convolution layer in a network definition.
Definition: NvInfer.h:1070
TRT_DEPRECATED DimsHW getPadding() const noexcept
Get the padding of the convolution. If the padding is asymmetric, the pre-padding is returned.
Definition: NvInfer.h:1173
TRT_DEPRECATED DimsHW getStride() const noexcept
Get the stride of the convolution.
Definition: NvInfer.h:1141
TRT_DEPRECATED DimsHW getDilation() const noexcept
Get the dilation for a convolution.
Definition: NvInfer.h:1280
void setStrideNd(Dims stride) noexcept
Set the multi-dimension stride of the convolution.
Definition: NvInfer.h:1398
void setKernelSizeNd(Dims kernelSize) noexcept
Set the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1373
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1307
Weights getBiasWeights() const noexcept
Get the bias weights for the convolution.
Definition: NvInfer.h:1252
int32_t getNbGroups() const noexcept
Get the number of groups of the convolution.
Definition: NvInfer.h:1203
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1348
TRT_DEPRECATED void setStride(DimsHW stride) noexcept
Get the stride of the convolution.
Definition: NvInfer.h:1131
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the convolution.
Definition: NvInfer.h:1438
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the convolution.
Definition: NvInfer.h:1408
TRT_DEPRECATED void setPadding(DimsHW padding) noexcept
Set the padding of the convolution.
Definition: NvInfer.h:1161
Weights getKernelWeights() const noexcept
Get the kernel weights of the convolution.
Definition: NvInfer.h:1227
void setPaddingNd(Dims padding) noexcept
Set the multi-dimension padding of the convolution.
Definition: NvInfer.h:1426
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1462
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the convolution.
Definition: NvInfer.h:1217
void setDilationNd(Dims dilation) noexcept
Set the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1452
Dims getPostPadding() const noexcept
Get the post-padding.
Definition: NvInfer.h:1334
TRT_DEPRECATED void setDilation(DimsHW dilation) noexcept
Set the dilation for a convolution.
Definition: NvInfer.h:1268
void setNbGroups(int32_t nbGroups) noexcept
Set the number of groups for a convolution.
Definition: NvInfer.h:1193
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1360
int32_t getNbOutputMaps() const noexcept
Get the number of output maps for the convolution.
Definition: NvInfer.h:1115
void setPrePadding(Dims padding) noexcept
Set the multi-dimension pre-padding of the convolution.
Definition: NvInfer.h:1297
virtual ~IConvolutionLayer() noexcept=default
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the convolution.
Definition: NvInfer.h:1242
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1383
void setNbOutputMaps(int32_t nbOutputMaps) noexcept
Set the number of output maps for the convolution.
Definition: NvInfer.h:1105
TRT_DEPRECATED void setKernelSize(DimsHW kernelSize) noexcept
Set the HW kernel size of the convolution.
Definition: NvInfer.h:1081
void setPostPadding(Dims padding) noexcept
Set the multi-dimension post-padding of the convolution.
Definition: NvInfer.h:1324
TRT_DEPRECATED DimsHW getKernelSize() const noexcept
Get the HW kernel size of the convolution.
Definition: NvInfer.h:1093
An engine for executing inference on a built network, with functionally unsafe features.
Definition: NvInferRuntime.h:1543
A deconvolution layer in a network definition.
Definition: NvInfer.h:2475
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the deconvolution.
Definition: NvInfer.h:2653
TRT_DEPRECATED void setStride(DimsHW stride) noexcept
Set the stride of the deconvolution.
Definition: NvInfer.h:2538
void setNbOutputMaps(int32_t nbOutputMaps) noexcept
Set the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2512
Weights getKernelWeights() const noexcept
Get the kernel weights for the deconvolution.
Definition: NvInfer.h:2638
void setPrePadding(Dims padding) noexcept
Set the multi-dimension pre-padding of the deconvolution.
Definition: NvInfer.h:2681
TRT_DEPRECATED DimsHW getPadding() const noexcept
Get the padding of the deconvolution.
Definition: NvInfer.h:2584
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2797
int32_t getNbGroups() const noexcept
Get the number of groups for a deconvolution.
Definition: NvInfer.h:2614
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2861
Weights getBiasWeights() const noexcept
Get the bias weights for the deconvolution.
Definition: NvInfer.h:2663
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the deconvolution.
Definition: NvInfer.h:2628
void setDilationNd(Dims dilation) noexcept
Set the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2851
TRT_DEPRECATED DimsHW getStride() const noexcept
Get the stride of the deconvolution.
Definition: NvInfer.h:2550
TRT_DEPRECATED void setPadding(DimsHW padding) noexcept
Set the padding of the deconvolution.
Definition: NvInfer.h:2570
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:2719
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2770
void setKernelSizeNd(Dims kernelSize) noexcept
Set the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2760
virtual ~IDeconvolutionLayer() noexcept=default
TRT_DEPRECATED void setKernelSize(DimsHW kernelSize) noexcept
Set the HW kernel size of the convolution.
Definition: NvInfer.h:2488
void setStrideNd(Dims stride) noexcept
Set the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2787
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2827
void setNbGroups(int32_t nbGroups) noexcept
Set the number of groups for a deconvolution.
Definition: NvInfer.h:2604
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:2733
void setPaddingNd(Dims padding) noexcept
Set the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2815
TRT_DEPRECATED DimsHW getKernelSize() const noexcept
Get the HW kernel size of the deconvolution.
Definition: NvInfer.h:2500
void setPostPadding(Dims padding) noexcept
Set the multi-dimension post-padding of the deconvolution.
Definition: NvInfer.h:2709
int32_t getNbOutputMaps() const noexcept
Get the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2522
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:2691
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:2745
A Dequantize layer in a network definition.
Definition: NvInfer.h:6154
virtual ~IDequantizeLayer() noexcept=default
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:6164
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:6175
An Einsum layer in a network.
Definition: NvInfer.h:6221
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:6232
virtual ~IEinsumLayer() noexcept=default
char const * getEquation() const noexcept
Return the equation.
Definition: NvInfer.h:6242
A elementwise layer in a network definition.
Definition: NvInfer.h:2936
virtual ~IElementWiseLayer() noexcept=default
apiv::VElementWiseLayer * mImpl
Definition: NvInfer.h:2965
ElementWiseOperation getOperation() const noexcept
Get the binary operation for the layer.
Definition: NvInfer.h:2959
void setOperation(ElementWiseOperation op) noexcept
Set the binary operation for the layer.
Definition: NvInfer.h:2947
Reference counted application-implemented error reporting interface for TensorRT objects.
Definition: NvInferRuntimeBase.h:694
Generate an output tensor with specified mode.
Definition: NvInfer.h:5852
FillOperation getOperation() const noexcept
Get the fill operation for the layer.
Definition: NvInfer.h:5898
void setOperation(FillOperation op) noexcept
Set the fill operation for the layer.
Definition: NvInfer.h:5888
void setDimensions(Dims dimensions) noexcept
Set the output tensor's dimensions.
Definition: NvInfer.h:5863
void setBeta(double beta) noexcept
Set the beta parameter.
Definition: NvInfer.h:5951
double getAlpha() const noexcept
Get the value of alpha parameter.
Definition: NvInfer.h:5932
void setAlpha(double alpha) noexcept
Set the alpha parameter.
Definition: NvInfer.h:5917
Dims getDimensions() const noexcept
Get the output tensor's dimensions.
Definition: NvInfer.h:5878
double getBeta() const noexcept
Get the value of beta parameter.
Definition: NvInfer.h:5966
virtual ~IFillLayer() noexcept=default
A fully connected layer in a network definition. This layer expects an input tensor of three or more ...
Definition: NvInfer.h:1519
virtual ~IFullyConnectedLayer() noexcept=default
void setNbOutputChannels(int32_t nbOutputs) noexcept
Set the number of output channels K from the fully connected layer.
Definition: NvInfer.h:1528
Weights getKernelWeights() const noexcept
Get the kernel weights.
Definition: NvInfer.h:1558
void setBiasWeights(Weights weights) noexcept
Set the bias weights.
Definition: NvInfer.h:1570
void setKernelWeights(Weights weights) noexcept
Set the kernel weights, given as a KxC matrix in row-major order.
Definition: NvInfer.h:1548
int32_t getNbOutputChannels() const noexcept
Get the number of output channels K from the fully connected layer.
Definition: NvInfer.h:1538
Weights getBiasWeights() const noexcept
Get the bias weights.
Definition: NvInfer.h:1580
A Gather layer in a network definition. Supports several kinds of gathering.
Definition: NvInfer.h:3071
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:3082
void setNbElementWiseDims(int32_t elementWiseDims) noexcept
Set the number of leading dimensions of indices tensor to be handled elementwise. The gathering of in...
Definition: NvInfer.h:3114
apiv::VGatherLayer * mImpl
Definition: NvInfer.h:3150
int32_t getNbElementWiseDims() const noexcept
Get the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:3124
void setMode(GatherMode mode) noexcept
Set the gather mode.
Definition: NvInfer.h:3134
int32_t getGatherAxis() const noexcept
Get the axis to gather on.
Definition: NvInfer.h:3093
GatherMode getMode() const noexcept
Get the gather mode.
Definition: NvInfer.h:3144
virtual ~IGatherLayer() noexcept=default
Application-implemented class for controlling allocation on the GPU.
Definition: NvInferRuntimeBase.h:367
A GridSample layer in a network definition.
Definition: NvInfer.h:6439
void setInterpolationMode(InterpolationMode mode) noexcept
Set the grid sample interpolation mode.
Definition: NvInfer.h:6446
bool setSampleMode(SampleMode mode) noexcept
Set the sample mode.
Definition: NvInfer.h:6492
void setAlignCorners(bool alignCorners) noexcept
Set the align corners mode.
Definition: NvInfer.h:6468
apiv::VGridSampleLayer * mImpl
Definition: NvInfer.h:6510
SampleMode getSampleMode() const noexcept
Get the sample mode.
Definition: NvInfer.h:6504
InterpolationMode getInterpolationMode() const noexcept
Get the grid sample interpolation mode.
Definition: NvInfer.h:6458
bool getAlignCorners() const noexcept
Get the align corners mode.
Definition: NvInfer.h:6480
virtual ~IGridSampleLayer() noexcept=default
Class to handle library allocated memory that is accessible to the user.
Definition: NvInferRuntime.h:144
A layer that represents the identity function.
Definition: NvInfer.h:4698
apiv::VIdentityLayer * mImpl
Definition: NvInfer.h:4700
virtual ~IIdentityLayer() noexcept=default
Definition: NvInfer.h:5353
IIfConditional * getConditional() const noexcept
Return pointer to the IIfConditional associated with this boundary layer.
Definition: NvInfer.h:5356
virtual ~IIfConditionalBoundaryLayer() noexcept=default
Definition: NvInfer.h:5423
IIfConditionalInputLayer * addInput(ITensor &input) noexcept
Add an If-conditional input.
Definition: NvInfer.h:5462
char const * getName() const noexcept
Return the name of the conditional.
Definition: NvInfer.h:5487
virtual ~IIfConditional() noexcept=default
IConditionLayer * setCondition(ITensor &condition) noexcept
Set the condition tensor for this If-Conditional construct.
Definition: NvInfer.h:5434
IIfConditionalOutputLayer * addOutput(ITensor &trueSubgraphOutput, ITensor &falseSubgraphOutput) noexcept
Add an If-conditional output.
Definition: NvInfer.h:5450
void setName(char const *name) noexcept
Set the name of the conditional.
Definition: NvInfer.h:5477
Definition: NvInfer.h:5383
virtual ~IIfConditionalOutputLayer() noexcept=default
Application-implemented interface for calibration.
Definition: NvInfer.h:8278
virtual int32_t getBatchSize() const noexcept=0
Get the batch size used for calibration batches.
Definition: NvInfer.h:8361
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8366
virtual ~IInt8EntropyCalibrator2() noexcept=default
Definition: NvInfer.h:8343
virtual ~IInt8EntropyCalibrator() noexcept=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8348
Definition: NvInfer.h:8396
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8401
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:8378
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8383
virtual ~IInt8MinMaxCalibrator() noexcept=default
Definition: NvInfer.h:5615
virtual ~IIteratorLayer() noexcept=default
void setReverse(bool reverse) noexcept
Definition: NvInfer.h:5634
bool getReverse() const noexcept
True if and only if reversing input.
Definition: NvInfer.h:5640
int32_t getAxis() const noexcept
Get axis being iterated over.
Definition: NvInfer.h:5624
void setAxis(int32_t axis) noexcept
Set axis to iterate over.
Definition: NvInfer.h:5618
A LRN layer in a network definition.
Definition: NvInfer.h:2079
int32_t getWindowSize() const noexcept
Get the LRN window size.
Definition: NvInfer.h:2100
float getAlpha() const noexcept
Get the LRN alpha value.
Definition: NvInfer.h:2121
void setWindowSize(int32_t windowSize) noexcept
Set the LRN window size.
Definition: NvInfer.h:2090
void setK(float k) noexcept
Set the LRN K value.
Definition: NvInfer.h:2153
void setAlpha(float alpha) noexcept
Set the LRN alpha value.
Definition: NvInfer.h:2111
void setBeta(float beta) noexcept
Set the LRN beta value.
Definition: NvInfer.h:2132
virtual ~ILRNLayer() noexcept=default
float getBeta() const noexcept
Get the LRN beta value.
Definition: NvInfer.h:2142
float getK() const noexcept
Get the LRN K value.
Definition: NvInfer.h:2163
Base class for all layer classes in a network definition.
Definition: NvInfer.h:543
bool precisionIsSet() const noexcept
whether the computational precision has been set for this layer
Definition: NvInfer.h:683
void setMetadata(char const *metadata) noexcept
Set the metadata for this layer.
Definition: NvInfer.h:788
void setPrecision(DataType dataType) noexcept
Set the computational precision of this layer.
Definition: NvInfer.h:659
void setName(char const *name) noexcept
Set the name of a layer.
Definition: NvInfer.h:564
void resetPrecision() noexcept
reset the computational precision for this layer
Definition: NvInfer.h:693
int32_t getNbInputs() const noexcept
Get the number of inputs of a layer.
Definition: NvInfer.h:582
char const * getMetadata() const noexcept
Get the metadata of the layer.
Definition: NvInfer.h:801
DataType getOutputType(int32_t index) const noexcept
get the output type of this layer
Definition: NvInfer.h:745
DataType getPrecision() const noexcept
get the computational precision of this layer
Definition: NvInfer.h:671
char const * getName() const noexcept
Return the name of a layer.
Definition: NvInfer.h:574
int32_t getNbOutputs() const noexcept
Get the number of outputs of a layer.
Definition: NvInfer.h:603
bool outputTypeIsSet(int32_t index) const noexcept
whether the output type has been set for this layer
Definition: NvInfer.h:758
ITensor * getOutput(int32_t index) const noexcept
Get the layer output corresponding to the given index.
Definition: NvInfer.h:614
void setInput(int32_t index, ITensor &tensor) noexcept
Replace an input of this layer with a specific tensor.
Definition: NvInfer.h:631
void resetOutputType(int32_t index) noexcept
reset the output type for this layer
Definition: NvInfer.h:770
ITensor * getInput(int32_t index) const noexcept
Get the layer input corresponding to the given index.
Definition: NvInfer.h:595
void setOutputType(int32_t index, DataType dataType) noexcept
Set the output type of this layer.
Definition: NvInfer.h:731
LayerType getType() const noexcept
Return the type of a layer.
Definition: NvInfer.h:550
virtual ~ILayer() noexcept=default
Application-implemented logging interface for the builder, refitter and runtime.
Definition: NvInferRuntimeBase.h:505
Definition: NvInfer.h:5334
virtual ~ILoopBoundaryLayer() noexcept=default
ILoop * getLoop() const noexcept
Return pointer to ILoop associated with this boundary layer.
Definition: NvInfer.h:5337
Definition: NvInfer.h:5656
void setName(char const *name) noexcept
Set the name of the loop.
Definition: NvInfer.h:5725
ITripLimitLayer * addTripLimit(ITensor &tensor, TripLimit limit) noexcept
Add a trip-count limiter, based on the given tensor.
Definition: NvInfer.h:5685
IIteratorLayer * addIterator(ITensor &tensor, int32_t axis=0, bool reverse=false) noexcept
Return layer that subscripts tensor by loop iteration.
Definition: NvInfer.h:5698
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:5710
virtual ~ILoop() noexcept=default
char const * getName() const noexcept
Return the name of the loop.
Definition: NvInfer.h:5735
IRecurrenceLayer * addRecurrence(ITensor &initialValue) noexcept
Create a recurrence layer for this loop with initialValue as its first input.
Definition: NvInfer.h:5664
Definition: NvInfer.h:5544
virtual ~ILoopOutputLayer() noexcept=default
int32_t getAxis() const noexcept
Get axis being concatenated over.
Definition: NvInfer.h:5569
LoopOutput getLoopOutput() const noexcept
Definition: NvInfer.h:5546
void setAxis(int32_t axis) noexcept
Set where to insert the contenation axis. Ignored if getLoopOutput() is kLAST_VALUE.
Definition: NvInfer.h:5563
Layer that represents a Matrix Multiplication.
Definition: NvInfer.h:4591
apiv::VMatrixMultiplyLayer * mImpl
Definition: NvInfer.h:4617
virtual ~IMatrixMultiplyLayer() noexcept=default
MatrixOperation getOperation(int32_t index) const noexcept
Get the operation for an input tensor.
Definition: NvInfer.h:4611
void setOperation(int32_t index, MatrixOperation op) noexcept
Set the operation for an input tensor.
Definition: NvInfer.h:4599
A non-maximum suppression layer in a network definition.
Definition: NvInfer.h:6582
virtual ~INMSLayer() noexcept=default
void setTopKBoxLimit(int32_t limit) noexcept
Set the TopK box limit parameter for the layer.
Definition: NvInfer.h:6619
void setBoundingBoxFormat(BoundingBoxFormat fmt) noexcept
Set the bounding box format parameter for the layer.
Definition: NvInfer.h:6593
BoundingBoxFormat getBoundingBoxFormat() const noexcept
Get the bounding box format parameter for the layer.
Definition: NvInfer.h:6605
apiv::VNMSLayer * mImpl
Definition: NvInfer.h:6655
int32_t getTopKBoxLimit() const noexcept
Get the TopK box limit parameter for the layer.
Definition: NvInfer.h:6629
A network definition for input to the builder.
Definition: NvInfer.h:6863
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:7617
IConvolutionLayer * addConvolutionNd(ITensor &input, int32_t nbOutputMaps, Dims kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a multi-dimension convolution layer to the network.
Definition: NvInfer.h:7778
IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:8076
IConcatenationLayer * addConcatenation(ITensor *const *inputs, int32_t nbInputs) noexcept
Add a concatenation layer to the network.
Definition: NvInfer.h:7079
TRT_DEPRECATED IDeconvolutionLayer * addDeconvolution(ITensor &input, int32_t nbOutputMaps, DimsHW kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a deconvolution layer to the network.
Definition: NvInfer.h:7102
IShuffleLayer * addShuffle(ITensor &input) noexcept
Add a shuffle layer to the network.
Definition: NvInfer.h:7183
INormalizationLayer * addNormalization(ITensor &input, ITensor &scale, ITensor &bias, uint32_t axesMask) noexcept
Add a normalization layer to the network.
Definition: NvInfer.h:8221
void setName(char const *name) noexcept
Sets the name of the network.
Definition: NvInfer.h:7660
ILRNLayer * addLRN(ITensor &input, int32_t window, float alpha, float beta, float k) noexcept
Add a LRN layer to the network.
Definition: NvInfer.h:7022
ITopKLayer * addTopK(ITensor &input, TopKOperation op, int32_t k, uint32_t reduceAxes) noexcept
Add a TopK layer to the network.
Definition: NvInfer.h:7358
IAssertionLayer * addAssertion(ITensor &condition, char const *message) noexcept
Add an assertion layer to the network.
Definition: NvInfer.h:7960
ICastLayer * addCast(ITensor &input, DataType toType) noexcept
Add a cast layer.
Definition: NvInfer.h:7571
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:7857
char const * getName() const noexcept
Returns the name associated with the network.
Definition: NvInfer.h:7674
TRT_DEPRECATED bool hasExplicitPrecision() const noexcept
True if network is an explicit precision network.
Definition: NvInfer.h:7887
IParametricReLULayer * addParametricReLU(ITensor &input, ITensor &slope) noexcept
Add a parametric ReLU layer to the network.
Definition: NvInfer.h:7756
ITensor * getOutput(int32_t index) const noexcept
Get the output tensor specified by the given index.
Definition: NvInfer.h:7284
ITensor * getInput(int32_t index) const noexcept
Get the input tensor specified by the given index.
Definition: NvInfer.h:7254
bool unmarkOutputForShapes(ITensor &tensor) noexcept
Undo markOutputForShapes.
Definition: NvInfer.h:7738
IFillLayer * addFill(Dims dimensions, FillOperation op) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7983
ILoop * addLoop() noexcept
Add a loop to the network.
Definition: NvInfer.h:7903
IDeconvolutionLayer * addDeconvolutionNd(ITensor &input, int32_t nbOutputMaps, Dims kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a multi-dimension deconvolution layer to the network.
Definition: NvInfer.h:7820
IActivationLayer * addActivation(ITensor &input, ActivationType type) noexcept
Add an activation layer to the network.
Definition: NvInfer.h:6984
virtual ~INetworkDefinition() noexcept=default
virtual IBuilder & getBuilder() const noexcept
Return the builder from which this INetworkDefinition was created.
Definition: NvInfer.h:8233
INMSLayer * addNMS(ITensor &boxes, ITensor &scores, ITensor &maxOutputBoxesPerClass) noexcept
Add a non-maximum suppression layer to the network.
Definition: NvInfer.h:8178
ILayer * getLayer(int32_t index) const noexcept
Get the layer specified by the given index.
Definition: NvInfer.h:7226
TRT_DEPRECATED IRNNv2Layer * addRNNv2(ITensor &input, int32_t layerCount, int32_t hiddenSize, int32_t maxSeqLen, RNNOperation op) noexcept
Add an layerCount deep RNN layer to the network with hiddenSize internal states that can take a batch...
Definition: NvInfer.h:7541
TRT_DEPRECATED IFullyConnectedLayer * addFullyConnected(ITensor &input, int32_t nbOutputs, Weights kernelWeights, Weights biasWeights) noexcept
Add a fully connected layer to the network.
Definition: NvInfer.h:6964
IIfConditional * addIfConditional() noexcept
Add an If-conditional layer to the network.
Definition: NvInfer.h:8130
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:8057
IReverseSequenceLayer * addReverseSequence(ITensor &input, ITensor &sequenceLens) noexcept
Add a ReverseSequence layer to the network.
Definition: NvInfer.h:8195
int32_t getNbInputs() const noexcept
Get the number of inputs in the network.
Definition: NvInfer.h:7238
bool hasImplicitBatchDimension() const noexcept
Query whether the network was created with an implicit batch dimension.
Definition: NvInfer.h:7708
IReduceLayer * addReduce(ITensor &input, ReduceOperation operation, uint32_t reduceAxes, bool keepDimensions) noexcept
Add a reduce layer to the network.
Definition: NvInfer.h:7323
IUnaryLayer * addUnary(ITensor &input, UnaryOperation operation) noexcept
Add a unary layer to the network.
Definition: NvInfer.h:7152
IGridSampleLayer * addGridSample(ITensor &input, ITensor &grid) noexcept
Add a GridSample layer to the network.
Definition: NvInfer.h:8160
void removeTensor(ITensor &tensor) noexcept
remove a tensor from the network definition.
Definition: NvInfer.h:7586
ISelectLayer * addSelect(ITensor &condition, ITensor &thenInput, ITensor &elseInput) noexcept
Add a select layer to the network.
Definition: NvInfer.h:7943
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:8096
int32_t getNbLayers() const noexcept
Get the number of layers in the network.
Definition: NvInfer.h:7212
apiv::VNetworkDefinition * mImpl
Definition: NvInfer.h:8239
IPoolingLayer * addPoolingNd(ITensor &input, PoolingType type, Dims windowSize) noexcept
Add a multi-dimension pooling layer to the network.
Definition: NvInfer.h:7798
bool markOutputForShapes(ITensor &tensor) noexcept
Enable tensor's value to be computed by IExecutionContext::getShapeBinding.
Definition: NvInfer.h:7726
IOneHotLayer * addOneHot(ITensor &indices, ITensor &values, ITensor &depth, int32_t axis) noexcept
Add a OneHot layer to the network.
Definition: NvInfer.h:7200
TRT_DEPRECATED IPaddingLayer * addPadding(ITensor &input, DimsHW prePadding, DimsHW postPadding) noexcept
Add a padding layer to the network.
Definition: NvInfer.h:7169
IScaleLayer * addScale(ITensor &input, ScaleMode mode, Weights shift, Weights scale, Weights power) noexcept
Add a Scale layer to the network.
Definition: NvInfer.h:7049
void unmarkOutput(ITensor &tensor) noexcept
unmark a tensor as a network output.
Definition: NvInfer.h:7598
IIdentityLayer * addIdentity(ITensor &input) noexcept
Add an identity layer.
Definition: NvInfer.h:7556
IGatherLayer * addGatherV2(ITensor &data, ITensor &indices, GatherMode mode) noexcept
Add gather with specified mode, axis=0 and nbElementWiseDims=0.
Definition: NvInfer.h:7390
TRT_DEPRECATED IConvolutionLayer * addConvolution(ITensor &input, int32_t nbOutputMaps, DimsHW kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a convolution layer to the network.
Definition: NvInfer.h:6941
IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:8115
IElementWiseLayer * addElementWise(ITensor &input1, ITensor &input2, ElementWiseOperation op) noexcept
Add an elementwise layer to the network.
Definition: NvInfer.h:7130
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:8042
ISliceLayer * addSlice(ITensor &input, Dims start, Dims size, Dims stride) noexcept
Add a slice layer to the network.
Definition: NvInfer.h:7636
IConstantLayer * addConstant(Dims dimensions, Weights weights) noexcept
Add a constant layer to the network.
Definition: NvInfer.h:7471
IRaggedSoftMaxLayer * addRaggedSoftMax(ITensor &input, ITensor &bounds) noexcept
Add a RaggedSoftMax layer to the network.
Definition: NvInfer.h:7408
IShapeLayer * addShape(ITensor &input) noexcept
Add a shape layer to the network.
Definition: NvInfer.h:7690
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:7374
TRT_DEPRECATED IPoolingLayer * addPooling(ITensor &input, PoolingType type, DimsHW windowSize) noexcept
Add a pooling layer to the network.
Definition: NvInfer.h:7003
TRT_DEPRECATED void destroy() noexcept
Destroy this INetworkDefinition object.
Definition: NvInfer.h:7296
IResizeLayer * addResize(ITensor &input) noexcept
Add a resize layer to the network.
Definition: NvInfer.h:7873
IMatrixMultiplyLayer * addMatrixMultiply(ITensor &input0, MatrixOperation op0, ITensor &input1, MatrixOperation op1) noexcept
Add a MatrixMultiply layer to the network.
Definition: NvInfer.h:7429
ISoftMaxLayer * addSoftMax(ITensor &input) noexcept
Add a SoftMax layer to the network.
Definition: NvInfer.h:7062
IEinsumLayer * addEinsum(ITensor *const *inputs, int32_t nbInputs, char const *equation) noexcept
Add an Einsum layer to the network.
Definition: NvInfer.h:8144
void markOutput(ITensor &tensor) noexcept
Mark a tensor as a network output.
Definition: NvInfer.h:6918
INonZeroLayer * addNonZero(ITensor &input) noexcept
Add a nonzero layer to the network.
Definition: NvInfer.h:7444
int32_t getNbOutputs() const noexcept
Get the number of outputs in the network.
Definition: NvInfer.h:7268
TRT_DEPRECATED IPaddingLayer * addPaddingNd(ITensor &input, Dims prePadding, Dims postPadding) noexcept
Add a padding layer to the network. Only 2D padding is currently supported.
Definition: NvInfer.h:8000
bool setWeightsName(Weights weights, char const *name) noexcept
Associate a name with all current uses of the given weights.
Definition: NvInfer.h:8023
Forward declaration of IEngineInspector for use by other interfaces.
Definition: NvInferRuntime.h:43
Definition: NvInfer.h:4643
virtual ~INonZeroLayer() noexcept=default
A normalization layer in a network definition.
Definition: NvInfer.h:6742
float getEpsilon() const noexcept
Get the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6759
int32_t getNbGroups() const noexcept
Get the number of groups used to split the channels for the normalization calculation.
Definition: NvInfer.h:6806
uint32_t getAxes() const noexcept
Get the axes value used for the normalization calculation.
Definition: NvInfer.h:6777
virtual ~INormalizationLayer() noexcept=default
void setEpsilon(float eps) noexcept
Set the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6750
DataType getComputePrecision() const noexcept
Get the compute precision of this layer.
Definition: NvInfer.h:6833
apiv::VNormalizationLayer * mImpl
Definition: NvInfer.h:6839
void setAxes(uint32_t axesMask) noexcept
Set the reduction axes for the normalization calculation.
Definition: NvInfer.h:6768
void setComputePrecision(DataType type) noexcept
Set the compute precision of this layer.
Definition: NvInfer.h:6824
void setNbGroups(int32_t nbGroups) noexcept
Set the number of groups used to split the channels in the normalization calculation.
Definition: NvInfer.h:6797
A OneHot layer in a network definition.
Definition: NvInfer.h:6404
apiv::VOneHotLayer * mImpl
Definition: NvInfer.h:6425
void setAxis(int32_t axis) noexcept
Set the axis parameter.
Definition: NvInfer.h:6411
int32_t getAxis() const noexcept
Get the value of the axis parameter.
Definition: NvInfer.h:6419
Optimization profile for dynamic input dimensions and shape tensors.
Definition: NvInferRuntime.h:1293
Layer that represents a padding operation.
Definition: NvInfer.h:3874
Dims getPostPaddingNd() const noexcept
Get the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3975
TRT_DEPRECATED DimsHW getPrePadding() const noexcept
Get the padding that is applied at the start of the tensor.
Definition: NvInfer.h:3897
TRT_DEPRECATED void setPostPadding(DimsHW padding) noexcept
Set the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3911
virtual ~IPaddingLayer() noexcept=default
TRT_DEPRECATED void setPrePadding(DimsHW padding) noexcept
Set the padding that is applied at the start of the tensor.
Definition: NvInfer.h:3885
Dims getPrePaddingNd() const noexcept
Get the padding that is applied at the start of the tensor.
Definition: NvInfer.h:3949
TRT_DEPRECATED DimsHW getPostPadding() const noexcept
Get the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3923
void setPostPaddingNd(Dims padding) noexcept
Set the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3963
void setPrePaddingNd(Dims padding) noexcept
Set the padding that is applied at the start of the tensor.
Definition: NvInfer.h:3937
apiv::VPaddingLayer * mImpl
Definition: NvInfer.h:3981
Layer that represents a parametric ReLU operation.
Definition: NvInfer.h:4808
apiv::VParametricReLULayer * mImpl
Definition: NvInfer.h:4810
virtual ~IParametricReLULayer() noexcept=default
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferRuntimeCommon.h:50
Plugin class for user-implemented layers.
Definition: NvInferRuntimePlugin.h:98
Layer type for pluginV2.
Definition: NvInfer.h:3640
virtual ~IPluginV2Layer() noexcept=default
apiv::VPluginV2Layer * mImpl
Definition: NvInfer.h:3653
IPluginV2 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:3647
A Pooling layer in a network definition.
Definition: NvInfer.h:1741
TRT_DEPRECATED DimsHW getStride() const noexcept
Get the stride for pooling.
Definition: NvInfer.h:1814
PoolingType getPoolingType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1760
void setWindowSizeNd(Dims windowSize) noexcept
Set the multi-dimension window size for pooling.
Definition: NvInfer.h:1993
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1980
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:1956
TRT_DEPRECATED void setStride(DimsHW stride) noexcept
Set the stride for pooling.
Definition: NvInfer.h:1802
bool getAverageCountExcludesPadding() const noexcept
Get whether average pooling uses as a denominator the overlap area between the window and the unpadde...
Definition: NvInfer.h:1900
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1928
void setPoolingType(PoolingType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1750
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1969
TRT_DEPRECATED void setWindowSize(DimsHW windowSize) noexcept
Set the window size for pooling.
Definition: NvInfer.h:1774
Dims getWindowSizeNd() const noexcept
Get the multi-dimension window size for pooling.
Definition: NvInfer.h:2003
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:1889
void setPaddingNd(Dims padding) noexcept
Set the multi-dimension padding for pooling.
Definition: NvInfer.h:2047
void setPrePadding(Dims padding) noexcept
Set the multi-dimension pre-padding for pooling.
Definition: NvInfer.h:1918
float getBlendFactor() const noexcept
Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1872
Dims getStrideNd() const noexcept
Get the multi-dimension stride for pooling.
Definition: NvInfer.h:2028
virtual ~IPoolingLayer() noexcept=default
Dims getPaddingNd() const noexcept
Get the multi-dimension padding for pooling.
Definition: NvInfer.h:2059
TRT_DEPRECATED DimsHW getWindowSize() const noexcept
Get the window size for pooling.
Definition: NvInfer.h:1786
TRT_DEPRECATED DimsHW getPadding() const noexcept
Get the padding for pooling.
Definition: NvInfer.h:1844
void setStrideNd(Dims stride) noexcept
Set the multi-dimension stride for pooling.
Definition: NvInfer.h:2018
void setPostPadding(Dims padding) noexcept
Set the multi-dimension post-padding for pooling.
Definition: NvInfer.h:1946
TRT_DEPRECATED void setPadding(DimsHW padding) noexcept
Set the padding for pooling.
Definition: NvInfer.h:1830
void setBlendFactor(float blendFactor) noexcept
Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1859
A Quantize layer in a network definition.
Definition: NvInfer.h:6068
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:6089
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:6078
virtual ~IQuantizeLayer() noexcept=default
An RNN layer in a network definition, version 2.
Definition: NvInfer.h:3350
void setDirection(RNNDirection op) noexcept
Set the direction of the RNN layer.
Definition: NvInfer.h:3450
void setBiasForGate(int32_t layerIndex, RNNGateType gate, bool isW, Weights bias) noexcept
Set the bias parameters for an individual gate in the RNN.
Definition: NvInfer.h:3552
void setCellState(ITensor &cell) noexcept
Set the initial cell state of the LSTM with the provided cell ITensor.
Definition: NvInfer.h:3610
int32_t getDataLength() const noexcept
Get the embedding length of the RNN.
Definition: NvInfer.h:3364
void setInputMode(RNNInputMode op) noexcept
Set the input mode of the RNN layer.
Definition: NvInfer.h:3425
Weights getBiasForGate(int32_t layerIndex, RNNGateType gate, bool isW) const noexcept
Get the bias parameters for an individual gate in the RNN.
Definition: NvInfer.h:3562
void setWeightsForGate(int32_t layerIndex, RNNGateType gate, bool isW, Weights weights) noexcept
Set the weight parameters for an individual gate in the RNN.
Definition: NvInfer.h:3518
void setOperation(RNNOperation op) noexcept
Set the operation of the RNN layer.
Definition: NvInfer.h:3405
Weights getWeightsForGate(int32_t layerIndex, RNNGateType gate, bool isW) const noexcept
Get the weight parameters for an individual gate in the RNN.
Definition: NvInfer.h:3528
RNNDirection getDirection() const noexcept
Get the direction of the RNN layer.
Definition: NvInfer.h:3460
void setSequenceLengths(ITensor &seqLengths) noexcept
Specify individual sequence lengths in the batch with the ITensor pointed to by seqLengths.
Definition: NvInfer.h:3383
RNNInputMode getInputMode() const noexcept
Get the input mode of the RNN layer.
Definition: NvInfer.h:3435
ITensor * getHiddenState() const noexcept
Get the initial hidden state of the RNN.
Definition: NvInfer.h:3590
ITensor * getCellState() const noexcept
Get the initial cell state of the RNN.
Definition: NvInfer.h:3620
int32_t getMaxSeqLength() const noexcept
Get the maximum sequence length of the RNN.
Definition: NvInfer.h:3360
int32_t getLayerCount() const noexcept
Get the layer count of the RNN.
Definition: NvInfer.h:3352
apiv::VRNNv2Layer * mImpl
Definition: NvInfer.h:3626
ITensor * getSequenceLengths() const noexcept
Get the sequence lengths specified for the RNN.
Definition: NvInfer.h:3395
RNNOperation getOperation() const noexcept
Get the operation of the RNN layer.
Definition: NvInfer.h:3415
virtual ~IRNNv2Layer() noexcept=default
int32_t getHiddenSize() const noexcept
Get the hidden size of the RNN.
Definition: NvInfer.h:3356
void setHiddenState(ITensor &hidden) noexcept
Set the initial hidden state of the RNN with the provided hidden ITensor.
Definition: NvInfer.h:3580
A RaggedSoftmax layer in a network definition.
Definition: NvInfer.h:4664
apiv::VRaggedSoftMaxLayer * mImpl
Definition: NvInfer.h:4666
virtual ~IRaggedSoftMaxLayer() noexcept=default
Definition: NvInfer.h:5499
virtual ~IRecurrenceLayer() noexcept=default
Layer that represents a reduction across a non-bool tensor.
Definition: NvInfer.h:3796
void setKeepDimensions(bool keepDimensions) noexcept
Set the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:3843
void setOperation(ReduceOperation op) noexcept
Set the reduce operation for the layer.
Definition: NvInfer.h:3803
ReduceOperation getOperation() const noexcept
Get the reduce operation for the layer.
Definition: NvInfer.h:3813
virtual ~IReduceLayer() noexcept=default
uint32_t getReduceAxes() const noexcept
Get the axes over which to reduce for the layer.
Definition: NvInfer.h:3833
void setReduceAxes(uint32_t reduceAxes) noexcept
Set the axes over which to reduce.
Definition: NvInfer.h:3823
apiv::VReduceLayer * mImpl
Definition: NvInfer.h:3859
bool getKeepDimensions() const noexcept
Get the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:3853
A resize layer in a network definition.
Definition: NvInfer.h:5000
void setSelectorForSinglePixel(ResizeSelector selector) noexcept
Set coordinate selector function when resized to single pixel.
Definition: NvInfer.h:5189
void setOutputDimensions(Dims dimensions) noexcept
Set the output dimensions.
Definition: NvInfer.h:5020
void setNearestRounding(ResizeRoundMode value) noexcept
Set rounding mode for nearest neighbor resize.
Definition: NvInfer.h:5213
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:5079
void setCubicCoeff(float A) noexcept
Set the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:5245
ResizeMode getResizeMode() const noexcept
Get resize mode for an input tensor.
Definition: NvInfer.h:5101
void setScales(float const *scales, int32_t nbScales) noexcept
Set the resize scales.
Definition: NvInfer.h:5060
void setResizeMode(ResizeMode resizeMode) noexcept
Set resize mode for an input tensor.
Definition: NvInfer.h:5091
float getCubicCoeff() const noexcept
Get the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:5255
ResizeSelector getSelectorForSinglePixel() const noexcept
Get the coordinate selector function when resized to single pixel.
Definition: NvInfer.h:5199
TRT_DEPRECATED bool getAlignCorners() const noexcept
True if align corners has been set.
Definition: NvInfer.h:5129
void setCoordinateTransformation(ResizeCoordinateTransformation coordTransform) noexcept
Set coordinate transformation function.
Definition: NvInfer.h:5164
void setExcludeOutside(bool excludeFlag) noexcept
Set the state for excluding outside pixels.
Definition: NvInfer.h:5268
Dims getOutputDimensions() const noexcept
Get the output dimensions.
Definition: NvInfer.h:5030
ResizeRoundMode getNearestRounding() const noexcept
Get rounding mode for nearest neighbor resize.
Definition: NvInfer.h:5223
bool getExcludeOutside() const noexcept
Get the state for excluding outside pixels.
Definition: NvInfer.h:5278
TRT_DEPRECATED void setAlignCorners(bool alignCorners) noexcept
Set whether to align corners while resizing.
Definition: NvInfer.h:5117
ResizeCoordinateTransformation getCoordinateTransformation() const noexcept
Get coordinate transformation function.
Definition: NvInfer.h:5174
A ReverseSequence layer in a network definition.
Definition: NvInfer.h:6671
void setSequenceAxis(int32_t sequenceAxis) noexcept
Set the sequence axis. Default is 0.
Definition: NvInfer.h:6704
int32_t getBatchAxis() const noexcept
Return the batch axis. Return 1 if no batch axis was set.
Definition: NvInfer.h:6691
apiv::VReverseSequenceLayer * mImpl
Definition: NvInfer.h:6720
int32_t getSequenceAxis() const noexcept
Return the sequence axis. Return 0 if no sequence axis was set.
Definition: NvInfer.h:6714
void setBatchAxis(int32_t batchAxis) noexcept
Set the batch axis. Default is 1.
Definition: NvInfer.h:6681
virtual ~IReverseSequenceLayer() noexcept=default
A Scale layer in a network definition.
Definition: NvInfer.h:2223
Weights getScale() const noexcept
Get the scale value.
Definition: NvInfer.h:2280
Weights getPower() const noexcept
Get the power value.
Definition: NvInfer.h:2300
void setScale(Weights scale) noexcept
Set the scale value.
Definition: NvInfer.h:2270
void setPower(Weights power) noexcept
Set the power value.
Definition: NvInfer.h:2290
ScaleMode getMode() const noexcept
Get the scale mode.
Definition: NvInfer.h:2240
void setShift(Weights shift) noexcept
Set the shift value.
Definition: NvInfer.h:2250
void setChannelAxis(int32_t channelAxis) noexcept
Set the channel axis.
Definition: NvInfer.h:2336
Weights getShift() const noexcept
Get the shift value.
Definition: NvInfer.h:2260
virtual ~IScaleLayer() noexcept=default
void setMode(ScaleMode mode) noexcept
Set the scale mode.
Definition: NvInfer.h:2230
int32_t getChannelAxis() const noexcept
Get the channel axis.
Definition: NvInfer.h:2315
A scatter layer in a network definition. Supports several kinds of scattering.
Definition: NvInfer.h:6331
void setMode(ScatterMode mode) noexcept
Set the scatter mode.
Definition: NvInfer.h:6338
apiv::VScatterLayer * mImpl
Definition: NvInfer.h:6372
void setAxis(int32_t axis) noexcept
Set the axis used by ScatterMode::kELEMENTS.
Definition: NvInfer.h:6358
int32_t getAxis() const noexcept
Get the axis.
Definition: NvInfer.h:6366
ScatterMode getMode() const noexcept
Get the scatter mode.
Definition: NvInfer.h:6348
virtual ~IScatterLayer() noexcept=default
Definition: NvInfer.h:5749
virtual ~ISelectLayer() noexcept=default
Layer type for getting shape of a tensor.
Definition: NvInfer.h:4394
virtual ~IShapeLayer() noexcept=default
apiv::VShapeLayer * mImpl
Definition: NvInfer.h:4396
Layer type for shuffling data.
Definition: NvInfer.h:4009
apiv::VShuffleLayer * mImpl
Definition: NvInfer.h:4164
void setReshapeDimensions(Dims dimensions) noexcept
Set the reshaped dimensions.
Definition: NvInfer.h:4057
void setFirstTranspose(Permutation permutation) noexcept
Set the permutation applied by the first transpose operation.
Definition: NvInfer.h:4020
void setSecondTranspose(Permutation permutation) noexcept
Set the permutation applied by the second transpose operation.
Definition: NvInfer.h:4117
Dims getReshapeDimensions() const noexcept
Get the reshaped dimensions.
Definition: NvInfer.h:4070
Permutation getFirstTranspose() const noexcept
Get the permutation applied by the first transpose operation.
Definition: NvInfer.h:4032
virtual ~IShuffleLayer() noexcept=default
Permutation getSecondTranspose() const noexcept
Get the permutation applied by the second transpose operation.
Definition: NvInfer.h:4129
bool getZeroIsPlaceholder() const noexcept
Get meaning of 0 in reshape dimensions.
Definition: NvInfer.h:4158
void setZeroIsPlaceholder(bool zeroIsPlaceholder) noexcept
Set meaning of 0 in reshape dimensions.
Definition: NvInfer.h:4145
Slices an input tensor into an output tensor based on the offset and strides.
Definition: NvInfer.h:4242
void setMode(SliceMode mode) noexcept
Set the slice mode.
Definition: NvInfer.h:4336
apiv::VSliceLayer * mImpl
Definition: NvInfer.h:4377
virtual ~ISliceLayer() noexcept=default
void setStride(Dims stride) noexcept
Set the stride for computing the output slice data.
Definition: NvInfer.h:4311
void setStart(Dims start) noexcept
Set the start offset that the slice layer uses to create the output slice.
Definition: NvInfer.h:4253
Dims getStart() const noexcept
Get the start offset for the slice layer.
Definition: NvInfer.h:4268
void setSize(Dims size) noexcept
Set the dimensions of the output slice.
Definition: NvInfer.h:4282
Dims getSize() const noexcept
Get dimensions of the output slice.
Definition: NvInfer.h:4297
SliceMode getMode() const noexcept
Get the slice mode.
Definition: NvInfer.h:4346
Dims getStride() const noexcept
Get the stride for the output slice.
Definition: NvInfer.h:4326
A Softmax layer in a network definition.
Definition: NvInfer.h:2368
void setAxes(uint32_t axes) noexcept
Set the axis along which softmax is computed. Currently, only one axis can be set.
Definition: NvInfer.h:2400
uint32_t getAxes() const noexcept
Get the axis along which softmax occurs.
Definition: NvInfer.h:2410
virtual ~ISoftMaxLayer() noexcept=default
A tensor in a network definition.
Definition: NvInfer.h:175
bool setDynamicRange(float min, float max) noexcept
Set dynamic range for the tensor.
Definition: NvInfer.h:277
void setAllowedFormats(TensorFormats formats) noexcept
Set allowed formats for this tensor. By default all formats are allowed. Shape tensors (for which isS...
Definition: NvInfer.h:413
TensorLocation getLocation() const noexcept
Get the storage location of a tensor.
Definition: NvInfer.h:341
void resetDynamicRange() noexcept
Undo effect of setDynamicRange.
Definition: NvInfer.h:374
void setName(char const *name) noexcept
Set the tensor name.
Definition: NvInfer.h:191
bool isExecutionTensor() const noexcept
Whether the tensor is an execution tensor.
Definition: NvInfer.h:484
void setType(DataType type) noexcept
Set the data type of a tensor.
Definition: NvInfer.h:250
bool dynamicRangeIsSet() const noexcept
Query whether dynamic range is set.
Definition: NvInfer.h:366
void setLocation(TensorLocation location) noexcept
Set the storage location of a tensor.
Definition: NvInfer.h:356
char const * getName() const noexcept
Get the tensor name.
Definition: NvInfer.h:203
bool isShapeTensor() const noexcept
Whether the tensor is a shape tensor.
Definition: NvInfer.h:461
float getDynamicRangeMax() const noexcept
Get maximum of dynamic range.
Definition: NvInfer.h:394
bool isNetworkInput() const noexcept
Whether the tensor is a network input.
Definition: NvInfer.h:285
bool isNetworkOutput() const noexcept
Whether the tensor is a network output.
Definition: NvInfer.h:293
bool getBroadcastAcrossBatch() const noexcept
Check if tensor is broadcast across the batch.
Definition: NvInfer.h:331
void setBroadcastAcrossBatch(bool broadcastAcrossBatch) noexcept
Set whether to enable broadcast of tensor across the batch.
Definition: NvInfer.h:315
DataType getType() const noexcept
Get the data type of a tensor.
Definition: NvInfer.h:262
apiv::VTensor * mImpl
Definition: NvInfer.h:531
float getDynamicRangeMin() const noexcept
Get minimum of dynamic range.
Definition: NvInfer.h:384
virtual ~ITensor() noexcept=default
void setDimensionName(int32_t index, char const *name) noexcept
Name a dimension of an input tensor.
Definition: NvInfer.h:510
char const * getDimensionName(int32_t index) const noexcept
Get the name of an input dimension.
Definition: NvInfer.h:525
void setDimensions(Dims dimensions) noexcept
Set the dimensions of a tensor.
Definition: NvInfer.h:222
Dims getDimensions() const noexcept
Get the dimensions of a tensor.
Definition: NvInfer.h:235
TensorFormats getAllowedFormats() const noexcept
Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor,...
Definition: NvInfer.h:426
Class to handle tactic timing info collected from builder.
Definition: NvInfer.h:8877
bool combine(ITimingCache const &inputCache, bool ignoreMismatch) noexcept
Combine input timing cache into local instance.
Definition: NvInfer.h:8914
virtual ~ITimingCache() noexcept=default
apiv::VTimingCache * mImpl
Definition: NvInfer.h:8930
bool reset() noexcept
Empty the timing cache.
Definition: NvInfer.h:8924
Layer that represents a TopK reduction.
Definition: NvInfer.h:4434
void setK(int32_t k) noexcept
Set the static k value for the layer.
Definition: NvInfer.h:4465
void setReduceAxes(uint32_t reduceAxes) noexcept
Set which axes to reduce for the layer.
Definition: NvInfer.h:4489
TopKOperation getOperation() const noexcept
Get the operation for the layer.
Definition: NvInfer.h:4451
apiv::VTopKLayer * mImpl
Definition: NvInfer.h:4521
void setOperation(TopKOperation op) noexcept
Set the operation for the layer.
Definition: NvInfer.h:4441
int32_t getK() const noexcept
Get the k value for the layer.
Definition: NvInfer.h:4479
uint32_t getReduceAxes() const noexcept
Get the axes to reduce for the layer.
Definition: NvInfer.h:4499
virtual ~ITopKLayer() noexcept=default
Definition: NvInfer.h:5602
TripLimit getTripLimit() const noexcept
Definition: NvInfer.h:5604
virtual ~ITripLimitLayer() noexcept=default
Layer that represents an unary operation.
Definition: NvInfer.h:3721
void setOperation(UnaryOperation op) noexcept
Set the unary operation for the layer.
Definition: NvInfer.h:3730
apiv::VUnaryLayer * mImpl
Definition: NvInfer.h:3746
UnaryOperation getOperation() const noexcept
Get the unary operation for the layer.
Definition: NvInfer.h:3740
virtual ~IUnaryLayer() noexcept=default
An array of weights used as a layer parameter.
Definition: NvInferRuntime.h:126
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferSafeRuntime.h:961
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:1505
ResizeSelector
The coordinate selector when resize to single pixel output.
Definition: NvInfer.h:4905
@ kFORMULA
Use formula to map the original index.
@ kUPPER
Select the upper left pixel.
EngineCapability
List of supported engine capability flows.
Definition: NvInferRuntime.h:69
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:8941
ScaleMode
Controls how shift, scale and power are applied in a Scale layer.
Definition: NvInfer.h:2179
@ kUNIFORM
Identical coefficients across all elements of the tensor.
@ kCHANNEL
Per-channel coefficients.
uint32_t QuantizationFlags
Represents one or more QuantizationFlag values using binary OR operations.
Definition: NvInfer.h:8727
HardwareCompatibilityLevel
Definition: NvInfer.h:9057
constexpr int32_t EnumMax< RNNDirection >() noexcept
Definition: NvInfer.h:3271
BoundingBoxFormat
Representation of bounding box data used for the Boxes input tensor in INMSLayer.
Definition: NvInfer.h:6520
@ 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:8861
constexpr int32_t EnumMax< LayerType >() noexcept
Definition: NvInfer.h:110
constexpr int32_t EnumMax< RNNGateType >() noexcept
Definition: NvInfer.h:3332
constexpr int32_t EnumMax< CalibrationAlgoType >() noexcept
Definition: NvInfer.h:8261
UnaryOperation
Enumerates the unary operations that may be performed by a Unary layer.
Definition: NvInfer.h:3675
@ kISINF
Return true if input value equals +/- infinity for floating-point data type.
@ kCOSH
Hyperbolic cosine.
@ kACOSH
Inverse hyperbolic cosine.
@ kERF
Gauss error function.
@ 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:3783
constexpr int32_t EnumMax< TripLimit >() noexcept
Definition: NvInfer.h:5326
constexpr int32_t EnumMax< RNNInputMode >() noexcept
Definition: NvInfer.h:3303
RNNInputMode
Enumerates the RNN input modes that may occur with an RNN layer.
Definition: NvInfer.h:3292
@ kSKIP
No operation is performed on the first recurrent layer.
@ kLINEAR
Perform the normal matrix multiplication in the first recurrent layer.
ActivationType
Enumerates the types of activation to perform in an activation layer.
Definition: NvInfer.h:129
@ 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).