164 static constexpr int32_t kVALUE = 14;
202 mImpl->setName(name);
214 return mImpl->getName();
233 mImpl->setDimensions(dimensions);
247 return mImpl->getDimensions();
283 mImpl->setType(type);
298 return mImpl->getType();
306 return mImpl->isNetworkInput();
314 return mImpl->isNetworkOutput();
336 mImpl->setAllowedFormats(formats);
349 return mImpl->getAllowedFormats();
380 return mImpl->isShapeTensor();
401 return mImpl->isExecutionTensor();
427 mImpl->setDimensionName(index, name);
442 return mImpl->getDimensionName(index);
467 return mLayer->getType();
481 mLayer->setName(name);
491 return mLayer->getName();
499 return mLayer->getNbInputs();
512 return mLayer->getInput(index);
520 return mLayer->getNbOutputs();
530 return mLayer->getOutput(index);
547 return mLayer->setInput(index, tensor);
580 mLayer->setPrecision(dataType);
592 return mLayer->getPrecision();
606 return mLayer->precisionIsSet();
618 mLayer->resetPrecision();
668 mLayer->setOutputType(index, dataType);
683 return mLayer->getOutputType(index);
699 return mLayer->outputTypeIsSet(index);
713 return mLayer->resetOutputType(index);
731 mLayer->setMetadata(metadata);
744 return mLayer->getMetadata();
749 apiv::VLayer* mLayer;
926 static constexpr int32_t kVALUE = 4;
954 mImpl->setNbOutputMaps(nbOutputMaps);
964 return mImpl->getNbOutputMaps();
984 mImpl->setNbGroups(nbGroups);
994 return mImpl->getNbGroups();
1008 mImpl->setKernelWeights(weights);
1018 return mImpl->getKernelWeights();
1033 mImpl->setBiasWeights(weights);
1043 return mImpl->getBiasWeights();
1060 mImpl->setPrePadding(padding);
1070 return mImpl->getPrePadding();
1087 mImpl->setPostPadding(padding);
1097 return mImpl->getPostPadding();
1111 mImpl->setPaddingMode(paddingMode);
1123 return mImpl->getPaddingMode();
1136 mImpl->setKernelSizeNd(kernelSize);
1146 return mImpl->getKernelSizeNd();
1161 mImpl->setStrideNd(stride);
1171 return mImpl->getStrideNd();
1189 mImpl->setPaddingNd(padding);
1201 return mImpl->getPaddingNd();
1215 mImpl->setDilationNd(dilation);
1225 return mImpl->getDilationNd();
1274 mImpl->setActivationType(type);
1284 return mImpl->getActivationType();
1299 mImpl->setAlpha(alpha);
1313 mImpl->setBeta(beta);
1322 return mImpl->getAlpha();
1331 return mImpl->getBeta();
1361 static constexpr int32_t kVALUE = 3;
1388 mImpl->setPoolingType(type);
1398 return mImpl->getPoolingType();
1413 mImpl->setBlendFactor(blendFactor);
1426 return mImpl->getBlendFactor();
1440 mImpl->setAverageCountExcludesPadding(exclusive);
1451 return mImpl->getAverageCountExcludesPadding();
1469 mImpl->setPrePadding(padding);
1479 return mImpl->getPrePadding();
1497 mImpl->setPostPadding(padding);
1507 return mImpl->getPostPadding();
1520 mImpl->setPaddingMode(paddingMode);
1531 return mImpl->getPaddingMode();
1544 mImpl->setWindowSizeNd(windowSize);
1554 return mImpl->getWindowSizeNd();
1569 mImpl->setStrideNd(stride);
1579 return mImpl->getStrideNd();
1598 mImpl->setPaddingNd(padding);
1610 return mImpl->getPaddingNd();
1641 mImpl->setWindowSize(windowSize);
1651 return mImpl->getWindowSize();
1663 mImpl->setAlpha(alpha);
1673 return mImpl->getAlpha();
1685 mImpl->setBeta(beta);
1695 return mImpl->getBeta();
1717 return mImpl->getK();
1783 mImpl->setMode(mode);
1793 return mImpl->getMode();
1803 mImpl->setShift(shift);
1813 return mImpl->getShift();
1823 mImpl->setScale(scale);
1833 return mImpl->getScale();
1843 mImpl->setPower(power);
1853 return mImpl->getPower();
1868 return mImpl->getChannelAxis();
1889 mImpl->setChannelAxis(channelAxis);
1942 mImpl->setAxes(axes);
1952 return mImpl->getAxes();
1988 mImpl->setAxis(axis);
1998 return mImpl->getAxis();
2025 mImpl->setNbOutputMaps(nbOutputMaps);
2035 return mImpl->getNbOutputMaps();
2055 mImpl->setNbGroups(nbGroups);
2065 return mImpl->getNbGroups();
2079 mImpl->setKernelWeights(weights);
2089 return mImpl->getKernelWeights();
2104 mImpl->setBiasWeights(weights);
2114 return mImpl->getBiasWeights();
2131 mImpl->setPrePadding(padding);
2141 return mImpl->getPrePadding();
2158 mImpl->setPostPadding(padding);
2168 return mImpl->getPostPadding();
2182 mImpl->setPaddingMode(paddingMode);
2194 return mImpl->getPaddingMode();
2209 mImpl->setKernelSizeNd(kernelSize);
2219 return mImpl->getKernelSizeNd();
2236 mImpl->setStrideNd(stride);
2246 return mImpl->getStrideNd();
2264 mImpl->setPaddingNd(padding);
2276 return mImpl->getPaddingNd();
2302 mImpl->setDilationNd(dilation);
2312 return mImpl->getDilationNd();
2360 static constexpr int32_t kVALUE = 14;
2397 return mImpl->setOperation(op);
2409 return mImpl->getOperation();
2530 mImpl->setGatherAxis(axis);
2542 return mImpl->getGatherAxis();
2565 mImpl->setNbElementWiseDims(elementWiseDims);
2575 return mImpl->getNbElementWiseDims();
2585 mImpl->setMode(mode);
2595 return mImpl->getMode();
2678 mImpl->setOperation(op);
2688 return mImpl->getOperation();
2751 mImpl->setOperation(op);
2761 return mImpl->getOperation();
2771 mImpl->setReduceAxes(reduceAxes);
2781 return mImpl->getReduceAxes();
2791 mImpl->setKeepDimensions(keepDimensions);
2801 return mImpl->getKeepDimensions();
2835 mImpl->setPrePaddingNd(padding);
2847 return mImpl->getPrePaddingNd();
2861 mImpl->setPostPaddingNd(padding);
2873 return mImpl->getPostPaddingNd();
2923 mImpl->setFirstTranspose(permutation);
2935 return mImpl->getFirstTranspose();
2963 mImpl->setReshapeDimensions(dimensions);
2976 return mImpl->getReshapeDimensions();
3023 mImpl->setSecondTranspose(permutation);
3035 return mImpl->getSecondTranspose();
3051 return mImpl->setZeroIsPlaceholder(zeroIsPlaceholder);
3064 return mImpl->getZeroIsPlaceholder();
3175 mImpl->setStart(start);
3190 return mImpl->getStart();
3204 return mImpl->setSize(size);
3219 return mImpl->getSize();
3233 mImpl->setStride(stride);
3248 return mImpl->getStride();
3258 mImpl->setMode(mode);
3268 return mImpl->getMode();
3311 mImpl->setAxes(axes);
3326 return mImpl->getAxes();
3396 mImpl->setOperation(op);
3406 return mImpl->getOperation();
3434 return mImpl->getK();
3444 mImpl->setReduceAxes(reduceAxes);
3454 return mImpl->getReduceAxes();
3556 mImpl->setOperation(index, op);
3568 return mImpl->getOperation(index);
3693 mImpl->setToType(toType);
3704 return mImpl->getToType();
3733 mImpl->setWeights(weights);
3743 return mImpl->getWeights();
3755 mImpl->setDimensions(dimensions);
3767 return mImpl->getDimensions();
3813 static constexpr int32_t kVALUE = 3;
3867 static constexpr int32_t kVALUE = 3;
3897 static constexpr int32_t kVALUE = 2;
3933 static constexpr int32_t kVALUE = 4;
3996 return mImpl->setOutputDimensions(dimensions);
4006 return mImpl->getOutputDimensions();
4034 void setScales(
float const* scales, int32_t nbScales)
noexcept
4036 mImpl->setScales(scales, nbScales);
4053 int32_t
getScales(int32_t size,
float* scales)
const noexcept
4055 return mImpl->getScales(size, scales);
4067 mImpl->setResizeMode(interpolationMode);
4077 return mImpl->getResizeMode();
4112 mImpl->setCoordinateTransformation(coordTransform);
4122 return mImpl->getCoordinateTransformation();
4137 mImpl->setSelectorForSinglePixel(selector);
4147 return mImpl->getSelectorForSinglePixel();
4161 mImpl->setNearestRounding(value);
4171 return mImpl->getNearestRounding();
4193 mImpl->setCubicCoeff(A);
4203 return mImpl->getCubicCoeff();
4216 mImpl->setExcludeOutside(excludeFlag);
4226 return mImpl->getExcludeOutside();
4308 return mBoundary->getLoop();
4313 apiv::VLoopBoundaryLayer* mBoundary;
4331 return mBoundary->getConditional();
4336 apiv::VConditionalBoundaryLayer* mBoundary;
4420 return mImpl->setCondition(condition);
4438 return mImpl->addOutput(trueSubgraphOutput, falseSubgraphOutput);
4450 return mImpl->addInput(input);
4465 mImpl->setName(name);
4475 return mImpl->getName();
4545 return mImpl->getLoopOutput();
4562 mImpl->setAxis(axis);
4570 return mImpl->getAxis();
4619 return mImpl->getTripLimit();
4645 mImpl->setAxis(axis);
4653 return mImpl->getAxis();
4667 mImpl->setReverse(reverse);
4677 return mImpl->getReverse();
4706 return mImpl->addRecurrence(initialValue);
4727 return mImpl->addTripLimit(tensor, limit);
4740 return mImpl->addIterator(tensor, axis, reverse);
4753 return mImpl->addLoopOutput(tensor, outputKind, axis);
4768 mImpl->setName(name);
4778 return mImpl->getName();
4833 mImpl->setMessage(message);
4843 return mImpl->getMessage();
4945 mImpl->setDimensions(dimensions);
4960 return mImpl->getDimensions();
4970 mImpl->setOperation(op);
4980 return mImpl->getOperation();
4999 mImpl->setAlpha(alpha);
5014 return mImpl->getAlpha();
5033 mImpl->setBeta(beta);
5048 return mImpl->getBeta();
5109 mImpl->setAlphaInt64(alpha);
5124 return mImpl->getAlphaInt64();
5143 mImpl->setBetaInt64(beta);
5158 return mImpl->getBetaInt64();
5166 return mImpl->isAlphaBetaInt64();
5183 mImpl->setToType(toType);
5195 return mImpl->getToType();
5290 return mImpl->getAxis();
5301 mImpl->setAxis(axis);
5317 mImpl->setToType(toType);
5329 return mImpl->getToType();
5421 return mImpl->getAxis();
5432 mImpl->setAxis(axis);
5448 mImpl->setToType(toType);
5460 return mImpl->getToType();
5515 mImpl->setToType(toType);
5528 return mImpl->getToType();
5541 mImpl->setScaleType(scaleType);
5554 return mImpl->getScaleType();
5567 mImpl->setAxis(axis);
5577 return mImpl->getAxis();
5590 mImpl->setBlockSize(size);
5600 return mImpl->getBlockSize();
5656 return mImpl->setEquation(equation);
5666 return mImpl->getEquation();
5765 mImpl->setMode(mode);
5775 return mImpl->getMode();
5785 mImpl->setAxis(axis);
5793 return mImpl->getAxis();
5837 mImpl->setAxis(axis);
5845 return mImpl->getAxis();
5874 mImpl->setInterpolationMode(mode);
5886 return mImpl->getInterpolationMode();
5896 mImpl->setAlignCorners(alignCorners);
5908 return mImpl->getAlignCorners();
5920 return mImpl->setSampleMode(mode);
5932 return mImpl->getSampleMode();
6026 mImpl->setBoundingBoxFormat(fmt);
6038 return mImpl->getBoundingBoxFormat();
6052 mImpl->setTopKBoxLimit(limit);
6062 return mImpl->getTopKBoxLimit();
6115 mImpl->setBatchAxis(batchAxis);
6125 return mImpl->getBatchAxis();
6138 mImpl->setSequenceAxis(sequenceAxis);
6148 return mImpl->getSequenceAxis();
6186 return mImpl->setEpsilon(eps);
6196 return mImpl->getEpsilon();
6206 return mImpl->setAxes(axesMask);
6216 return mImpl->getAxes();
6237 return mImpl->setNbGroups(nbGroups);
6247 return mImpl->getNbGroups();
6273 return mImpl->setComputePrecision(type);
6283 return mImpl->getComputePrecision();
6378 static constexpr int32_t kVALUE = 1;
6424 return mImpl->setOperation(op);
6436 return mImpl->getOperation();
6448 mImpl->setExclusive(exclusive);
6460 return mImpl->getExclusive();
6472 mImpl->setReverse(reverse);
6484 return mImpl->getReverse();
6551 return mImpl->addInput(name, type, dimensions);
6565 mImpl->markOutput(tensor);
6583 return mImpl->markDebug(tensor);
6599 return mImpl->unmarkDebug(tensor);
6609 return mImpl->isDebugTensor(tensor);
6631 return mImpl->markUnfusedTensorsAsDebugTensors();
6645 return mImpl->unmarkUnfusedTensorsAsDebugTensors();
6665 return mImpl->addActivation(input, type);
6684 return mImpl->addLRN(input, window, alpha, beta, k);
6710 return mImpl->addScale(input, mode, shift, scale, power);
6723 return mImpl->addSoftMax(input);
6740 return mImpl->addConcatenation(inputs, nbInputs);
6767 return mImpl->addElementWise(input1, input2, op);
6789 return mImpl->addUnary(input, operation);
6803 return mImpl->addShuffle(input);
6820 return mImpl->addOneHot(indices, values, depth, axis);
6832 return mImpl->getNbLayers();
6846 return mImpl->getLayer(index);
6858 return mImpl->getNbInputs();
6874 return mImpl->getInput(index);
6888 return mImpl->getNbOutputs();
6904 return mImpl->getOutput(index);
6931 return mImpl->addReduce(input, operation, reduceAxes, keepDimensions);
6963 return mImpl->addTopK(input, op, k, reduceAxes);
6979 return mImpl->addGather(data, indices, axis);
6995 return mImpl->addGatherV2(data, indices, mode);
7014 return mImpl->addRaggedSoftMax(input, bounds);
7036 return mImpl->addMatrixMultiply(input0, op0, input1, op1);
7050 return mImpl->addNonZero(input);
7074 return mImpl->addConstant(dimensions, weights);
7088 return mImpl->addIdentity(input);
7103 return mImpl->addCast(input, toType);
7118 mImpl->removeTensor(tensor);
7130 mImpl->unmarkOutput(tensor);
7149 return mImpl->addSlice(input, start, size, stride);
7173 mImpl->setName(name);
7187 return mImpl->getName();
7203 return mImpl->addShape(input);
7213 return mImpl->getFlags();
7225 return mImpl->getFlag(networkDefinitionCreationFlag);
7242 return mImpl->markOutputForShapes(tensor);
7254 return mImpl->unmarkOutputForShapes(tensor);
7272 return mImpl->addParametricReLU(input, slope);
7295 return mImpl->addConvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7314 return mImpl->addPoolingNd(input, type, windowSize);
7337 return mImpl->addDeconvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7374 return mImpl->addScaleNd(input, mode, shift, scale, power, channelAxis);
7390 return mImpl->addResize(input);
7404 return mImpl->addLoop();
7419 return mImpl->addIfConditional();
7458 return mImpl->addSelect(condition, thenInput, elseInput);
7475 return mImpl->addAssertion(condition, message);
7501 return mImpl->addFillV2(dimensions, op, outputType);
7517 return mImpl->addPaddingNd(input, prePadding, postPadding);
7541 return mImpl->setWeightsName(weights, name);
7560 mImpl->setErrorRecorder(recorder);
7575 return mImpl->getErrorRecorder();
7597 return mImpl->addDequantizeV2(input, scale, outputType);
7617 return mImpl->addScatter(data, indices, updates, mode);
7639 return mImpl->addQuantizeV2(input, scale, outputType);
7667 return mImpl->addDynamicQuantize(input, axis, blockSize, outputType, scaleType);
7682 return mImpl->addEinsum(inputs, nbInputs, equation);
7700 return mImpl->addGridSample(input, grid);
7718 return mImpl->addNMS(boxes, scores, maxOutputBoxesPerClass);
7735 return mImpl->addReverseSequence(input, sequenceLens);
7761 return mImpl->addNormalization(input, scale, bias, axesMask);
7783 return mImpl->addCumulative(input, axis, operation, exclusive, reverse);
7794 return mImpl->getBuilder();
7807 return mImpl->markWeightsRefittable(name);
7819 return mImpl->unmarkWeightsRefittable(name);
7832 return mImpl->areWeightsMarkedRefittable(name);
7851 return mImpl->addSqueeze(input, axes);
7872 return mImpl->addUnsqueeze(input, axes);
7917 static constexpr int32_t kVALUE = 2;
8157 static constexpr uint64_t kINVALID_TACTIC_HASH = UINT64_MAX;
8190 return mImpl->serialize();
8214 return mImpl->combine(inputCache, ignoreMismatch);
8224 return mImpl->reset();
8241 int64_t
queryKeys(TimingCacheKey* keyBuffer, int64_t capacity)
const noexcept
8243 return mImpl->queryKeys(keyBuffer, capacity);
8258 TimingCacheValue
query(TimingCacheKey
const& key)
const noexcept
8260 return mImpl->query(key);
8280 bool update(TimingCacheKey
const& key, TimingCacheValue
const& value)
noexcept
8282 return mImpl->update(key, value);
8403 static constexpr int32_t kVALUE = 3;
8455 static constexpr int32_t kVALUE = 3;
8517 static constexpr int32_t kVALUE = 4;
8556 virtual void phaseStart(
char const* phaseName,
char const* parentPhase, int32_t nbSteps)
noexcept = 0;
8570 virtual bool stepComplete(
char const* phaseName, int32_t step)
noexcept = 0;
8629 virtual
void setAvgTimingIterations(int32_t avgTiming) noexcept
8631 mImpl->setAvgTimingIterations(avgTiming);
8643 return mImpl->getAvgTimingIterations();
8656 mImpl->setEngineCapability(capability);
8668 return mImpl->getEngineCapability();
8685 mImpl->setFlags(builderFlags);
8697 return mImpl->getFlags();
8709 mImpl->clearFlag(builderFlag);
8721 mImpl->setFlag(builderFlag);
8733 return mImpl->getFlag(builderFlag);
8750 mImpl->setDeviceType(layer, deviceType);
8760 return mImpl->getDeviceType(layer);
8772 return mImpl->isDeviceTypeSet(layer);
8782 mImpl->resetDeviceType(layer);
8792 return mImpl->canRunOnDLA(layer);
8808 mImpl->setDLACore(dlaCore);
8818 return mImpl->getDLACore();
8829 mImpl->setDefaultDeviceType(deviceType);
8839 return mImpl->getDefaultDeviceType();
8861 return mImpl->setProfileStream(stream);
8873 return mImpl->getProfileStream();
8890 return mImpl->addOptimizationProfile(profile);
8903 return mImpl->getNbOptimizationProfiles();
8915 mImpl->setProfilingVerbosity(verbosity);
8928 return mImpl->getProfilingVerbosity();
8950 return mImpl->setTacticSources(tacticSources);
8965 return mImpl->getTacticSources();
8985 return mImpl->createTimingCache(blob, size);
9008 return mImpl->setTimingCache(cache, ignoreMismatch);
9018 return mImpl->getTimingCache();
9050 mImpl->setMemoryPoolLimit(pool, poolSize);
9069 return mImpl->getMemoryPoolLimit(pool);
9087 mImpl->setPreviewFeature(feature, enable);
9101 return mImpl->getPreviewFeature(feature);
9134 mImpl->setBuilderOptimizationLevel(level);
9146 return mImpl->getBuilderOptimizationLevel();
9163 mImpl->setHardwareCompatibilityLevel(hardwareCompatibilityLevel);
9176 return mImpl->getHardwareCompatibilityLevel();
9189 mImpl->setPluginsToSerialize(paths, nbPaths);
9202 return mImpl->getPluginToSerialize(index);
9212 return mImpl->getNbPluginsToSerialize();
9241 mImpl->setMaxAuxStreams(nbStreams);
9251 return mImpl->getMaxAuxStreams();
9267 return mImpl->setProgressMonitor(monitor);
9277 return mImpl->getProgressMonitor();
9293 mImpl->setRuntimePlatform(runtimePlatform);
9305 return mImpl->getRuntimePlatform();
9317 mImpl->setMaxNbTactics(maxNbTactics);
9329 return mImpl->getMaxNbTactics();
9345 return mImpl->setTilingOptimizationLevel(level);
9357 return mImpl->getTilingOptimizationLevel();
9373 return mImpl->setL2LimitForTiling(size);
9385 return mImpl->getL2LimitForTiling();
9404 return mImpl->setNbComputeCapabilities(maxNbComputeCapabilities);
9416 return mImpl->getNbComputeCapabilities();
9434 return mImpl->setComputeCapability(computeCapability, index);
9448 return mImpl->getComputeCapability(index);
9516 int32_t getMaxDLABatchSize() const noexcept
9518 return mImpl->getMaxDLABatchSize();
9526 return mImpl->getNbDLACores();
9544 mImpl->setGpuAllocator(allocator);
9558 return mImpl->createBuilderConfig();
9584 return mImpl->createNetworkV2(flags);
9599 return mImpl->createOptimizationProfile();
9618 mImpl->setErrorRecorder(recorder);
9633 return mImpl->getErrorRecorder();
9660 return mImpl->buildSerializedNetwork(network, config);
9682 return mImpl->isNetworkSupported(network, config);
9692 return mImpl->getLogger();
9708 return mImpl->setMaxThreads(maxThreads);
9722 return mImpl->getMaxThreads();
9732 return mImpl->getPluginRegistry();
9745extern "C" TENSORRTAPI void* createInferBuilder_INTERNAL(
void* logger, int32_t version)
noexcept;
#define TENSORRTAPI
Definition: NvInferRuntimeBase.h:69
#define NV_TENSORRT_VERSION
Definition: NvInferRuntimeBase.h:101
#define TRT_DEPRECATED
Definition: NvInferRuntimeBase.h:42
#define TRT_DEPRECATED_ENUM
Definition: NvInferRuntimeBase.h:43
Definition: NvInferRuntimeBase.h:216
static constexpr int32_t MAX_DIMS
The maximum rank (number of dimensions) supported for a tensor.
Definition: NvInferRuntimeBase.h:219
An Activation layer in a network definition.
Definition: NvInfer.h:1263
void setBeta(float beta) noexcept
Set the beta parameter (must be finite).
Definition: NvInfer.h:1311
void setActivationType(ActivationType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1272
ActivationType getActivationType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1282
float getAlpha() const noexcept
Get the alpha parameter.
Definition: NvInfer.h:1320
virtual ~IActivationLayer() noexcept=default
float getBeta() const noexcept
Get the beta parameter.
Definition: NvInfer.h:1329
void setAlpha(float alpha) noexcept
Set the alpha parameter (must be finite).
Definition: NvInfer.h:1297
An assertion layer in a network.
Definition: NvInfer.h:4821
void setMessage(char const *message) noexcept
Set the message to print if the assertion fails.
Definition: NvInfer.h:4831
char const * getMessage() const noexcept
Return the assertion message.
Definition: NvInfer.h:4841
virtual ~IAssertionLayer() noexcept=default
Holds properties for configuring a builder to produce an engine.
Definition: NvInfer.h:8617
void setMemoryPoolLimit(MemoryPoolType pool, std::size_t poolSize) noexcept
Set the memory size for the memory pool.
Definition: NvInfer.h:9048
bool setComputeCapability(ComputeCapability computeCapability, int32_t index) noexcept
Set one compute capability for runtime execution.
Definition: NvInfer.h:9432
nvinfer1::ITimingCache * createTimingCache(void const *blob, std::size_t size) const noexcept
Create timing cache.
Definition: NvInfer.h:8983
bool setNbComputeCapabilities(int32_t maxNbComputeCapabilities) noexcept
Set the number of compute capabilities.
Definition: NvInfer.h:9402
void setPreviewFeature(PreviewFeature feature, bool enable) noexcept
Enable or disable a specific preview feature.
Definition: NvInfer.h:9085
bool getPreviewFeature(PreviewFeature feature) const noexcept
Get status of preview feature.
Definition: NvInfer.h:9099
int32_t getBuilderOptimizationLevel() noexcept
Get builder optimization level.
Definition: NvInfer.h:9144
bool setTacticSources(TacticSources tacticSources) noexcept
Set tactic sources.
Definition: NvInfer.h:8948
void setPluginsToSerialize(char const *const *paths, int32_t nbPaths) noexcept
Set the plugin libraries to be serialized with version-compatible engines.
Definition: NvInfer.h:9187
bool setTilingOptimizationLevel(TilingOptimizationLevel level) noexcept
Set the Tiling optimization level.
Definition: NvInfer.h:9343
bool setL2LimitForTiling(int64_t size) noexcept
Set the L2 cache usage limit for Tiling optimization.
Definition: NvInfer.h:9371
std::size_t getMemoryPoolLimit(MemoryPoolType pool) const noexcept
Get the memory size limit of the memory pool.
Definition: NvInfer.h:9067
int32_t getDLACore() const noexcept
Get the DLA core that the engine executes on.
Definition: NvInfer.h:8816
int32_t getNbPluginsToSerialize() const noexcept
Get the number of plugin library paths to be serialized with version-compatible engines.
Definition: NvInfer.h:9210
void setDeviceType(ILayer const *layer, DeviceType deviceType) noexcept
Set the device that this layer must execute on.
Definition: NvInfer.h:8748
void setEngineCapability(EngineCapability capability) noexcept
Configure the builder to target specified EngineCapability flow.
Definition: NvInfer.h:8654
int32_t getMaxAuxStreams() const noexcept
Get the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9249
bool getFlag(BuilderFlag builderFlag) const noexcept
Returns true if the build mode flag is set.
Definition: NvInfer.h:8731
void setMaxNbTactics(int32_t maxNbTactics) noexcept
Set the maximum number of tactics to time when there is a choice of tactics.
Definition: NvInfer.h:9315
int64_t getL2LimitForTiling() const noexcept
Get the L2 cache usage limit for tiling optimization.
Definition: NvInfer.h:9383
void setProgressMonitor(IProgressMonitor *monitor) noexcept
Sets the progress monitor for building a network.
Definition: NvInfer.h:9265
void setProfilingVerbosity(ProfilingVerbosity verbosity) noexcept
Set verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:8913
int32_t getNbOptimizationProfiles() const noexcept
Get number of optimization profiles.
Definition: NvInfer.h:8901
nvinfer1::ITimingCache const * getTimingCache() const noexcept
Get the pointer to the timing cache from current IBuilderConfig.
Definition: NvInfer.h:9016
void reset() noexcept
Resets the builder configuration to defaults.
Definition: NvInfer.h:8847
bool setTimingCache(ITimingCache const &cache, bool ignoreMismatch) noexcept
Attach a timing cache to IBuilderConfig.
Definition: NvInfer.h:9006
char const * getPluginToSerialize(int32_t index) const noexcept
Get the plugin library path to be serialized with version-compatible engines.
Definition: NvInfer.h:9200
EngineCapability getEngineCapability() const noexcept
Query EngineCapability flow configured for the builder.
Definition: NvInfer.h:8666
RuntimePlatform getRuntimePlatform() const noexcept
Get the target platform for runtime execution.
Definition: NvInfer.h:9303
DeviceType getDefaultDeviceType() const noexcept
Get the default DeviceType which was set by setDefaultDeviceType.
Definition: NvInfer.h:8837
void setRuntimePlatform(RuntimePlatform runtimePlatform) noexcept
Set the target platform for runtime execution.
Definition: NvInfer.h:9291
int32_t getMaxNbTactics() const noexcept
Query the maximum number of tactics timed when there is a choice.
Definition: NvInfer.h:9327
BuilderFlags getFlags() const noexcept
Get the build mode flags for this builder config. Defaults to 0.
Definition: NvInfer.h:8695
void setFlags(BuilderFlags builderFlags) noexcept
Set the build mode flags to turn on builder options for this network.
Definition: NvInfer.h:8683
TacticSources getTacticSources() const noexcept
Get tactic sources.
Definition: NvInfer.h:8963
void resetDeviceType(ILayer const *layer) noexcept
reset the DeviceType for this layer
Definition: NvInfer.h:8780
ComputeCapability getComputeCapability(int32_t index) const noexcept
Get one compute capability for runtime execution.
Definition: NvInfer.h:9446
void setDLACore(int32_t dlaCore) noexcept
Sets the DLA core used by the network. Defaults to -1.
Definition: NvInfer.h:8806
HardwareCompatibilityLevel getHardwareCompatibilityLevel() const noexcept
Get the hardware compatibility level.
Definition: NvInfer.h:9174
int32_t getNbComputeCapabilities() const noexcept
Get the number of compute capabilities.
Definition: NvInfer.h:9414
void clearFlag(BuilderFlag builderFlag) noexcept
clear a single build mode flag.
Definition: NvInfer.h:8707
int32_t addOptimizationProfile(IOptimizationProfile const *profile) noexcept
Add an optimization profile.
Definition: NvInfer.h:8888
IProgressMonitor * getProgressMonitor() const noexcept
Definition: NvInfer.h:9275
apiv::VBuilderConfig * mImpl
Definition: NvInfer.h:9452
int32_t getAvgTimingIterations() const noexcept
Query the number of averaging iterations.
Definition: NvInfer.h:8641
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:8827
void setFlag(BuilderFlag builderFlag) noexcept
Set a single build mode flag.
Definition: NvInfer.h:8719
virtual ~IBuilderConfig() noexcept=default
DeviceType getDeviceType(ILayer const *layer) const noexcept
Get the device that this layer executes on.
Definition: NvInfer.h:8758
bool canRunOnDLA(ILayer const *layer) const noexcept
Checks if a layer can run on DLA.
Definition: NvInfer.h:8790
cudaStream_t getProfileStream() const noexcept
Get the CUDA stream that is used to profile this network.
Definition: NvInfer.h:8871
void setHardwareCompatibilityLevel(HardwareCompatibilityLevel hardwareCompatibilityLevel) noexcept
Set the hardware compatibility level.
Definition: NvInfer.h:9161
TilingOptimizationLevel getTilingOptimizationLevel() const noexcept
Get the Tiling optimization level.
Definition: NvInfer.h:9355
void setMaxAuxStreams(int32_t nbStreams) noexcept
Set the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9239
ProfilingVerbosity getProfilingVerbosity() const noexcept
Get verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:8926
bool isDeviceTypeSet(ILayer const *layer) const noexcept
whether the DeviceType has been explicitly set for this layer
Definition: NvInfer.h:8770
void setBuilderOptimizationLevel(int32_t level) noexcept
Set builder optimization level.
Definition: NvInfer.h:9132
void setProfileStream(const cudaStream_t stream) noexcept
Set the CUDA stream that is used to profile this network.
Definition: NvInfer.h:8859
Builds an engine from a network definition.
Definition: NvInfer.h:9505
int32_t getNbDLACores() const noexcept
Return the number of DLA engines available to this builder.
Definition: NvInfer.h:9524
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:9631
apiv::VBuilder * mImpl
Definition: NvInfer.h:9736
ILogger * getLogger() const noexcept
get the logger with which the builder was created
Definition: NvInfer.h:9690
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:9680
int32_t getMaxThreads() const noexcept
get the maximum number of threads that can be used by the builder.
Definition: NvInfer.h:9720
IPluginRegistry & getPluginRegistry() noexcept
get the local plugin registry that can be used by the builder.
Definition: NvInfer.h:9730
nvinfer1::IOptimizationProfile * createOptimizationProfile() noexcept
Create a new optimization profile.
Definition: NvInfer.h:9597
void setGpuAllocator(IGpuAllocator *allocator) noexcept
Set the GPU allocator.
Definition: NvInfer.h:9542
nvinfer1::INetworkDefinition * createNetworkV2(NetworkDefinitionCreationFlags flags) noexcept
Create a network definition object.
Definition: NvInfer.h:9582
nvinfer1::IBuilderConfig * createBuilderConfig() noexcept
Create a builder configuration object.
Definition: NvInfer.h:9556
void reset() noexcept
Resets the builder state to default values.
Definition: NvInfer.h:9639
bool setMaxThreads(int32_t maxThreads) noexcept
Set the maximum number of threads.
Definition: NvInfer.h:9706
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:9616
nvinfer1::IHostMemory * buildSerializedNetwork(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds and serializes a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:9658
virtual ~IBuilder() noexcept=default
A cast layer in a network.
Definition: NvInfer.h:3682
virtual ~ICastLayer() noexcept=default
apiv::VCastLayer * mImpl
Definition: NvInfer.h:3708
DataType getToType() const noexcept
Return cast layer output type.
Definition: NvInfer.h:3702
void setToType(DataType toType) noexcept
Set cast layer output type.
Definition: NvInfer.h:3691
A concatenation layer in a network definition.
Definition: NvInfer.h:1973
void setAxis(int32_t axis) noexcept
Set the axis along which concatenation occurs.
Definition: NvInfer.h:1986
int32_t getAxis() const noexcept
Get the axis along which concatenation occurs.
Definition: NvInfer.h:1996
virtual ~IConcatenationLayer() noexcept=default
This layer represents a condition input to an IIfConditional.
Definition: NvInfer.h:4345
virtual ~IConditionLayer() noexcept=default
Layer that represents a constant value.
Definition: NvInfer.h:3721
void setWeights(Weights weights) noexcept
Set the weights for the layer.
Definition: NvInfer.h:3731
Weights getWeights() const noexcept
Get the weights for the layer.
Definition: NvInfer.h:3741
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions for the layer.
Definition: NvInfer.h:3753
apiv::VConstantLayer * mImpl
Definition: NvInfer.h:3771
virtual ~IConstantLayer() noexcept=default
Dims getDimensions() const noexcept
Get the dimensions for the layer.
Definition: NvInfer.h:3765
A convolution layer in a network definition.
Definition: NvInfer.h:943
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1068
Weights getBiasWeights() const noexcept
Get the bias weights for the convolution.
Definition: NvInfer.h:1041
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1109
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1213
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the convolution.
Definition: NvInfer.h:1199
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the convolution.
Definition: NvInfer.h:1169
Weights getKernelWeights() const noexcept
Get the kernel weights of the convolution.
Definition: NvInfer.h:1016
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the convolution.
Definition: NvInfer.h:1159
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1223
int64_t getNbOutputMaps() const noexcept
Get the number of output maps for the convolution.
Definition: NvInfer.h:962
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the convolution.
Definition: NvInfer.h:1006
Dims getPostPadding() const noexcept
Get the post-padding.
Definition: NvInfer.h:1095
int64_t getNbGroups() const noexcept
Get the number of groups of the convolution.
Definition: NvInfer.h:992
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1121
virtual ~IConvolutionLayer() noexcept=default
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a convolution.
Definition: NvInfer.h:982
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output maps for the convolution.
Definition: NvInfer.h:952
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the convolution.
Definition: NvInfer.h:1031
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1144
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the convolution.
Definition: NvInfer.h:1187
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the convolution.
Definition: NvInfer.h:1058
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the convolution.
Definition: NvInfer.h:1085
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1134
Layer that represents a cumulative operation across a tensor.
Definition: NvInfer.h:6411
bool setOperation(CumulativeOperation op) noexcept
Set the cumulative operation for the layer.
Definition: NvInfer.h:6422
void setReverse(bool reverse) noexcept
Specify whether the cumulative operation should be applied backward.
Definition: NvInfer.h:6470
apiv::VCumulativeLayer * mImpl
Definition: NvInfer.h:6488
bool getExclusive() const noexcept
Get whether it is exclusive accumulation or inclusive accumulation.
Definition: NvInfer.h:6458
virtual ~ICumulativeLayer() noexcept=default
bool getReverse() const noexcept
Get the boolean that specifies whether the cumulative operation should be applied backward.
Definition: NvInfer.h:6482
void setExclusive(bool exclusive) noexcept
Set whether it is an exclusive accumulation or inclusive accumulation.
Definition: NvInfer.h:6446
CumulativeOperation getOperation() const noexcept
Get the cumulative operation for the layer.
Definition: NvInfer.h:6434
A deconvolution layer in a network definition.
Definition: NvInfer.h:2014
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the deconvolution.
Definition: NvInfer.h:2102
int64_t getNbGroups() const noexcept
Get the number of groups for a deconvolution.
Definition: NvInfer.h:2063
Weights getKernelWeights() const noexcept
Get the kernel weights for the deconvolution.
Definition: NvInfer.h:2087
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the deconvolution.
Definition: NvInfer.h:2129
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2244
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2310
Weights getBiasWeights() const noexcept
Get the bias weights for the deconvolution.
Definition: NvInfer.h:2112
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the deconvolution.
Definition: NvInfer.h:2077
int64_t getNbOutputMaps() const noexcept
Get the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2033
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2234
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:2166
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2217
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the deconvolution.
Definition: NvInfer.h:2156
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2207
virtual ~IDeconvolutionLayer() noexcept=default
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2262
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2023
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2274
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2300
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:2180
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a deconvolution.
Definition: NvInfer.h:2053
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:2139
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:2192
A Dequantize layer in a network definition.
Definition: NvInfer.h:5409
void setToType(DataType toType) noexcept
Set the Dequantize layer output type.
Definition: NvInfer.h:5446
virtual ~IDequantizeLayer() noexcept=default
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5419
DataType getToType() const noexcept
Return the Dequantize layer output type.
Definition: NvInfer.h:5458
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5430
A network layer to perform dynamic quantization.
Definition: NvInfer.h:5486
int32_t getAxis() const noexcept
Get the axis along which blocking occurs.
Definition: NvInfer.h:5575
int32_t getBlockSize() const noexcept
Get the size of the quantization block.
Definition: NvInfer.h:5598
DataType getScaleType() const noexcept
Return the scale factors data type.
Definition: NvInfer.h:5552
void setScaleType(DataType scaleType) noexcept
Set the data type of the scale factors used to quantize the data.
Definition: NvInfer.h:5539
DataType getToType() const noexcept
Return DynamicQuantizeLayer's quantized output type.
Definition: NvInfer.h:5526
virtual ~IDynamicQuantizeLayer() noexcept=default
void setToType(DataType toType) noexcept
Set DynamicQuantizeLayer's quantized output type.
Definition: NvInfer.h:5513
void setAxis(int32_t axis) noexcept
Set the axis along which block quantization occurs.
Definition: NvInfer.h:5565
void setBlockSize(int32_t size) noexcept
Set the size of the quantization block.
Definition: NvInfer.h:5588
An Einsum layer in a network.
Definition: NvInfer.h:5643
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:5654
virtual ~IEinsumLayer() noexcept=default
char const * getEquation() const noexcept
Return the equation.
Definition: NvInfer.h:5664
A elementwise layer in a network definition.
Definition: NvInfer.h:2384
virtual ~IElementWiseLayer() noexcept=default
apiv::VElementWiseLayer * mImpl
Definition: NvInfer.h:2413
ElementWiseOperation getOperation() const noexcept
Get the binary operation for the layer.
Definition: NvInfer.h:2407
void setOperation(ElementWiseOperation op) noexcept
Set the binary operation for the layer.
Definition: NvInfer.h:2395
Generate a tensor according to a specified mode.
Definition: NvInfer.h:4932
bool isAlphaBetaInt64() const noexcept
Return true if alpha/beta have type int64, false if they have type double.
Definition: NvInfer.h:5164
FillOperation getOperation() const noexcept
Get the fill operation for the layer.
Definition: NvInfer.h:4978
void setOperation(FillOperation op) noexcept
Set the fill operation for the layer.
Definition: NvInfer.h:4968
DataType getToType() const noexcept
Get the fill layer output type.
Definition: NvInfer.h:5193
void setAlphaInt64(int64_t alpha) noexcept
Set the alpha parameter with int64 datatype.
Definition: NvInfer.h:5107
void setBetaInt64(int64_t beta) noexcept
Set the beta parameter with int64 datatype.
Definition: NvInfer.h:5141
void setBeta(double beta) noexcept
Set the beta parameter.
Definition: NvInfer.h:5031
int64_t getAlphaInt64() const noexcept
Get the value of alpha parameter with int64 datatype.
Definition: NvInfer.h:5122
int64_t getBetaInt64() const noexcept
Get the value of beta parameter with int64 datatype.
Definition: NvInfer.h:5156
double getAlpha() const noexcept
Get the value of alpha parameter.
Definition: NvInfer.h:5012
void setDimensions(Dims const &dimensions) noexcept
Set the output tensor's dimensions.
Definition: NvInfer.h:4943
void setAlpha(double alpha) noexcept
Set the alpha parameter.
Definition: NvInfer.h:4997
void setToType(DataType toType) noexcept
Set the fill layer output type.
Definition: NvInfer.h:5181
Dims getDimensions() const noexcept
Get the output tensor's dimensions.
Definition: NvInfer.h:4958
double getBeta() const noexcept
Get the value of beta parameter.
Definition: NvInfer.h:5046
virtual ~IFillLayer() noexcept=default
A Gather layer in a network definition. Supports several kinds of gathering.
Definition: NvInfer.h:2517
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:2528
void setNbElementWiseDims(int32_t elementWiseDims) noexcept
Set the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2563
apiv::VGatherLayer * mImpl
Definition: NvInfer.h:2599
int32_t getNbElementWiseDims() const noexcept
Get the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2573
void setMode(GatherMode mode) noexcept
Set the gather mode.
Definition: NvInfer.h:2583
int32_t getGatherAxis() const noexcept
Get the axis to gather on.
Definition: NvInfer.h:2540
GatherMode getMode() const noexcept
Get the gather mode.
Definition: NvInfer.h:2593
virtual ~IGatherLayer() noexcept=default
A GridSample layer in a network definition.
Definition: NvInfer.h:5865
void setInterpolationMode(InterpolationMode mode) noexcept
Set the grid sample interpolation mode.
Definition: NvInfer.h:5872
bool setSampleMode(SampleMode mode) noexcept
Set the sample mode.
Definition: NvInfer.h:5918
void setAlignCorners(bool alignCorners) noexcept
Set the align corners mode.
Definition: NvInfer.h:5894
apiv::VGridSampleLayer * mImpl
Definition: NvInfer.h:5936
SampleMode getSampleMode() const noexcept
Get the sample mode.
Definition: NvInfer.h:5930
InterpolationMode getInterpolationMode() const noexcept
Get the grid sample interpolation mode.
Definition: NvInfer.h:5884
bool getAlignCorners() const noexcept
Get the align corners mode.
Definition: NvInfer.h:5906
virtual ~IGridSampleLayer() noexcept=default
Class to handle library allocated memory that is accessible to the user.
Definition: NvInferRuntime.h:142
A layer that represents the identity function.
Definition: NvInfer.h:3669
apiv::VIdentityLayer * mImpl
Definition: NvInfer.h:3671
virtual ~IIdentityLayer() noexcept=default
This is a base class for Conditional boundary layers.
Definition: NvInfer.h:4324
IIfConditional * getConditional() const noexcept
Get a pointer to the IIfConditional associated with this boundary layer.
Definition: NvInfer.h:4329
virtual ~IIfConditionalBoundaryLayer() noexcept=default
Helper for constructing conditionally-executed subgraphs.
Definition: NvInfer.h:4407
IIfConditionalInputLayer * addInput(ITensor &input) noexcept
Add an If-conditional input.
Definition: NvInfer.h:4448
char const * getName() const noexcept
Return the name of the conditional.
Definition: NvInfer.h:4473
virtual ~IIfConditional() noexcept=default
IConditionLayer * setCondition(ITensor &condition) noexcept
Set the condition tensor for this If-Conditional construct.
Definition: NvInfer.h:4418
IIfConditionalOutputLayer * addOutput(ITensor &trueSubgraphOutput, ITensor &falseSubgraphOutput) noexcept
Add an If-conditional output.
Definition: NvInfer.h:4436
void setName(char const *name) noexcept
Set the name of the conditional.
Definition: NvInfer.h:4463
This layer represents an output of an IIfConditional.
Definition: NvInfer.h:4362
virtual ~IIfConditionalOutputLayer() noexcept=default
A layer to do iterations.
Definition: NvInfer.h:4638
virtual ~IIteratorLayer() noexcept=default
void setReverse(bool reverse) noexcept
Set iteration order to be reverse.
Definition: NvInfer.h:4665
bool getReverse() const noexcept
Check if the iteration order is reverse.
Definition: NvInfer.h:4675
int32_t getAxis() const noexcept
Get axis being iterated over.
Definition: NvInfer.h:4651
void setAxis(int32_t axis) noexcept
Set axis to iterate over.
Definition: NvInfer.h:4643
A LRN layer in a network definition.
Definition: NvInfer.h:1628
int64_t getWindowSize() const noexcept
Get the LRN window size.
Definition: NvInfer.h:1649
float getAlpha() const noexcept
Get the LRN alpha value.
Definition: NvInfer.h:1671
void setWindowSize(int64_t windowSize) noexcept
Set the LRN window size.
Definition: NvInfer.h:1639
void setK(float k) noexcept
Set the LRN K value.
Definition: NvInfer.h:1705
void setAlpha(float alpha) noexcept
Set the LRN alpha value.
Definition: NvInfer.h:1661
void setBeta(float beta) noexcept
Set the LRN beta value.
Definition: NvInfer.h:1683
virtual ~ILRNLayer() noexcept=default
float getBeta() const noexcept
Get the LRN beta value.
Definition: NvInfer.h:1693
float getK() const noexcept
Get the LRN K value.
Definition: NvInfer.h:1715
Base class for all layer classes in a network definition.
Definition: NvInfer.h:458
TRT_DEPRECATED void setPrecision(DataType dataType) noexcept
Set the preferred or required computational precision of this layer in a weakly-typed network.
Definition: NvInfer.h:578
TRT_DEPRECATED void setOutputType(int32_t index, DataType dataType) noexcept
Set the output type of this layer in a weakly-typed network.
Definition: NvInfer.h:666
TRT_DEPRECATED bool precisionIsSet() const noexcept
whether the computational precision has been set for this layer
Definition: NvInfer.h:604
void setMetadata(char const *metadata) noexcept
Set the metadata for this layer.
Definition: NvInfer.h:729
TRT_DEPRECATED void resetOutputType(int32_t index) noexcept
reset the output type for this layer
Definition: NvInfer.h:711
void setName(char const *name) noexcept
Set the name of a layer.
Definition: NvInfer.h:479
int32_t getNbInputs() const noexcept
Get the number of inputs of a layer.
Definition: NvInfer.h:497
char const * getMetadata() const noexcept
Get the metadata of the layer.
Definition: NvInfer.h:742
DataType getOutputType(int32_t index) const noexcept
get the output type of this layer
Definition: NvInfer.h:681
DataType getPrecision() const noexcept
get the computational precision of this layer
Definition: NvInfer.h:590
TRT_DEPRECATED bool outputTypeIsSet(int32_t index) const noexcept
whether the output type has been set for this layer
Definition: NvInfer.h:697
char const * getName() const noexcept
Return the name of a layer.
Definition: NvInfer.h:489
int32_t getNbOutputs() const noexcept
Get the number of outputs of a layer.
Definition: NvInfer.h:518
ITensor * getOutput(int32_t index) const noexcept
Get the layer output corresponding to the given index.
Definition: NvInfer.h:528
void setInput(int32_t index, ITensor &tensor) noexcept
Replace an input of this layer with a specific tensor.
Definition: NvInfer.h:545
ITensor * getInput(int32_t index) const noexcept
Get the layer input corresponding to the given index.
Definition: NvInfer.h:510
LayerType getType() const noexcept
Return the type of a layer.
Definition: NvInfer.h:465
TRT_DEPRECATED void resetPrecision() noexcept
reset the computational precision for this layer
Definition: NvInfer.h:616
virtual ~ILayer() noexcept=default
Application-implemented logging interface for the builder, refitter and runtime.
Definition: NvInferRuntime.h:1052
This is a base class for Loop boundary layers.
Definition: NvInfer.h:4301
virtual ~ILoopBoundaryLayer() noexcept=default
ILoop * getLoop() const noexcept
Get a pointer to ILoop associated with this boundary layer.
Definition: NvInfer.h:4306
Helper for creating a recurrent subgraph.
Definition: NvInfer.h:4696
void setName(char const *name) noexcept
Set the name of the loop.
Definition: NvInfer.h:4766
ITripLimitLayer * addTripLimit(ITensor &tensor, TripLimit limit) noexcept
Add a trip-count limiter, based on the given tensor.
Definition: NvInfer.h:4725
IIteratorLayer * addIterator(ITensor &tensor, int32_t axis=0, bool reverse=false) noexcept
Return layer that subscripts tensor by loop iteration.
Definition: NvInfer.h:4738
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:4751
virtual ~ILoop() noexcept=default
char const * getName() const noexcept
Return the name of the loop.
Definition: NvInfer.h:4776
IRecurrenceLayer * addRecurrence(ITensor &initialValue) noexcept
Create a recurrence layer for this loop with initialValue as its first input.
Definition: NvInfer.h:4704
An ILoopOutputLayer is the sole way to get output from a loop.
Definition: NvInfer.h:4538
virtual ~ILoopOutputLayer() noexcept=default
int32_t getAxis() const noexcept
Get axis being concatenated over.
Definition: NvInfer.h:4568
LoopOutput getLoopOutput() const noexcept
Get which kind a loop output has.
Definition: NvInfer.h:4543
void setAxis(int32_t axis) noexcept
Set where to insert the contenation axis. Ignored if getLoopOutput() is kLAST_VALUE.
Definition: NvInfer.h:4560
Layer that represents a Matrix Multiplication.
Definition: NvInfer.h:3544
apiv::VMatrixMultiplyLayer * mImpl
Definition: NvInfer.h:3572
virtual ~IMatrixMultiplyLayer() noexcept=default
MatrixOperation getOperation(int32_t index) const noexcept
Get the operation for an input tensor.
Definition: NvInfer.h:3566
void setOperation(int32_t index, MatrixOperation op) noexcept
Set the operation for an input tensor.
Definition: NvInfer.h:3554
A non-maximum suppression layer in a network definition.
Definition: NvInfer.h:6013
virtual ~INMSLayer() noexcept=default
void setTopKBoxLimit(int32_t limit) noexcept
Set the TopK box limit parameter for the layer.
Definition: NvInfer.h:6050
void setBoundingBoxFormat(BoundingBoxFormat fmt) noexcept
Set the bounding box format parameter for the layer.
Definition: NvInfer.h:6024
BoundingBoxFormat getBoundingBoxFormat() const noexcept
Get the bounding box format parameter for the layer.
Definition: NvInfer.h:6036
apiv::VNMSLayer * mImpl
Definition: NvInfer.h:6086
int32_t getTopKBoxLimit() const noexcept
Get the TopK box limit parameter for the layer.
Definition: NvInfer.h:6060
A network definition for input to the builder.
Definition: NvInfer.h:6510
IConcatenationLayer * addConcatenation(ITensor *const *inputs, int32_t nbInputs) noexcept
Add a concatenation layer to the network.
Definition: NvInfer.h:6738
IShuffleLayer * addShuffle(ITensor &input) noexcept
Add a shuffle layer to the network.
Definition: NvInfer.h:6801
INormalizationLayer * addNormalization(ITensor &input, ITensor &scale, ITensor &bias, uint32_t axesMask) noexcept
Add a normalization layer to the network.
Definition: NvInfer.h:7759
void setName(char const *name) noexcept
Sets the name of the network.
Definition: NvInfer.h:7171
bool markDebug(ITensor &tensor) noexcept
Mark a tensor as a debug tensor.
Definition: NvInfer.h:6581
ILRNLayer * addLRN(ITensor &input, int64_t window, float alpha, float beta, float k) noexcept
Add a LRN layer to the network.
Definition: NvInfer.h:6682
ITopKLayer * addTopK(ITensor &input, TopKOperation op, int32_t k, uint32_t reduceAxes) noexcept
Add a TopK layer to the network.
Definition: NvInfer.h:6961
ICumulativeLayer * addCumulative(ITensor &input, ITensor &axis, CumulativeOperation operation, bool exclusive, bool reverse) noexcept
Add a cumulative layer to the network.
Definition: NvInfer.h:7781
IAssertionLayer * addAssertion(ITensor &condition, char const *message) noexcept
Add an assertion layer to the network.
Definition: NvInfer.h:7473
IConvolutionLayer * addConvolutionNd(ITensor &input, int64_t nbOutputMaps, Dims const &kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a multi-dimension convolution layer to the network.
Definition: NvInfer.h:7292
ICastLayer * addCast(ITensor &input, DataType toType) noexcept
Add a cast layer.
Definition: NvInfer.h:7101
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:7371
char const * getName() const noexcept
Returns the name associated with the network.
Definition: NvInfer.h:7185
IParametricReLULayer * addParametricReLU(ITensor &input, ITensor &slope) noexcept
Add a parametric ReLU layer to the network.
Definition: NvInfer.h:7270
ITensor * getOutput(int32_t index) const noexcept
Get the output tensor specified by the given index.
Definition: NvInfer.h:6902
ITensor * getInput(int32_t index) const noexcept
Get the input tensor specified by the given index.
Definition: NvInfer.h:6872
IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7595
bool unmarkOutputForShapes(ITensor &tensor) noexcept
Undo markOutputForShapes.
Definition: NvInfer.h:7252
IFillLayer * addFill(Dims const &dimensions, FillOperation op, DataType outputType) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7499
ILoop * addLoop() noexcept
Add a loop to the network.
Definition: NvInfer.h:7402
IDynamicQuantizeLayer * addDynamicQuantize(ITensor &input, int32_t axis, int32_t blockSize, DataType outputType, DataType scaleType) noexcept
Add a dynamic quantization layer to the network.
Definition: NvInfer.h:7664
bool markUnfusedTensorsAsDebugTensors() noexcept
Mark unfused tensors as debug tensors.
Definition: NvInfer.h:6629
IActivationLayer * addActivation(ITensor &input, ActivationType type) noexcept
Add an activation layer to the network.
Definition: NvInfer.h:6663
ISliceLayer * addSlice(ITensor &input, Dims const &start, Dims const &size, Dims const &stride) noexcept
Add a slice layer to the network.
Definition: NvInfer.h:7147
virtual ~INetworkDefinition() noexcept=default
virtual IBuilder & getBuilder() const noexcept
Return the builder from which this INetworkDefinition was created.
Definition: NvInfer.h:7792
INMSLayer * addNMS(ITensor &boxes, ITensor &scores, ITensor &maxOutputBoxesPerClass) noexcept
Add a non-maximum suppression layer to the network.
Definition: NvInfer.h:7716
ILayer * getLayer(int32_t index) const noexcept
Get the layer specified by the given index.
Definition: NvInfer.h:6844
bool getFlag(NetworkDefinitionCreationFlag networkDefinitionCreationFlag) const noexcept
Returns true if the network definition creation flag is set.
Definition: NvInfer.h:7223
IIfConditional * addIfConditional() noexcept
Add an if-then-else to the network.
Definition: NvInfer.h:7417
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:7573
ISqueezeLayer * addSqueeze(ITensor &input, ITensor &axes) noexcept
Add a squeeze layer to the network.
Definition: NvInfer.h:7849
IReverseSequenceLayer * addReverseSequence(ITensor &input, ITensor &sequenceLens) noexcept
Add a ReverseSequence layer to the network.
Definition: NvInfer.h:7733
int32_t getNbInputs() const noexcept
Get the number of inputs in the network.
Definition: NvInfer.h:6856
NetworkDefinitionCreationFlags getFlags() const noexcept
Get the network definition creation flags for this network definition object. Defaults to 0.
Definition: NvInfer.h:7211
IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7637
IReduceLayer * addReduce(ITensor &input, ReduceOperation operation, uint32_t reduceAxes, bool keepDimensions) noexcept
Add a reduce layer to the network.
Definition: NvInfer.h:6928
IUnaryLayer * addUnary(ITensor &input, UnaryOperation operation) noexcept
Add a unary layer to the network.
Definition: NvInfer.h:6787
IGridSampleLayer * addGridSample(ITensor &input, ITensor &grid) noexcept
Add a GridSample layer to the network.
Definition: NvInfer.h:7698
void removeTensor(ITensor &tensor) noexcept
remove a tensor from the network definition.
Definition: NvInfer.h:7116
bool areWeightsMarkedRefittable(char const *name) const noexcept
Whether the weight has been marked as refittable.
Definition: NvInfer.h:7830
ISelectLayer * addSelect(ITensor &condition, ITensor &thenInput, ITensor &elseInput) noexcept
Add a select layer to the network.
Definition: NvInfer.h:7456
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:7615
int32_t getNbLayers() const noexcept
Get the number of layers in the network.
Definition: NvInfer.h:6830
apiv::VNetworkDefinition * mImpl
Definition: NvInfer.h:7876
bool markOutputForShapes(ITensor &tensor) noexcept
Enable tensor's value to be computed by IExecutionContext::getShapeBinding.
Definition: NvInfer.h:7240
IOneHotLayer * addOneHot(ITensor &indices, ITensor &values, ITensor &depth, int32_t axis) noexcept
Add a OneHot layer to the network.
Definition: NvInfer.h:6818
IScaleLayer * addScale(ITensor &input, ScaleMode mode, Weights shift, Weights scale, Weights power) noexcept
Add a Scale layer to the network.
Definition: NvInfer.h:6708
void unmarkOutput(ITensor &tensor) noexcept
unmark a tensor as a network output.
Definition: NvInfer.h:7128
IIdentityLayer * addIdentity(ITensor &input) noexcept
Add an identity layer.
Definition: NvInfer.h:7086
IGatherLayer * addGatherV2(ITensor &data, ITensor &indices, GatherMode mode) noexcept
Add gather with specified mode, axis=0 and nbElementWiseDims=0.
Definition: NvInfer.h:6993
IElementWiseLayer * addElementWise(ITensor &input1, ITensor &input2, ElementWiseOperation op) noexcept
Add an elementwise layer to the network.
Definition: NvInfer.h:6765
IConstantLayer * addConstant(Dims const &dimensions, Weights weights) noexcept
Add a constant layer to the network.
Definition: NvInfer.h:7072
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:7558
IPoolingLayer * addPoolingNd(ITensor &input, PoolingType type, Dims const &windowSize) noexcept
Add a multi-dimension pooling layer to the network.
Definition: NvInfer.h:7312
IRaggedSoftMaxLayer * addRaggedSoftMax(ITensor &input, ITensor &bounds) noexcept
Add a RaggedSoftMax layer to the network.
Definition: NvInfer.h:7012
IShapeLayer * addShape(ITensor &input) noexcept
Add a shape layer to the network.
Definition: NvInfer.h:7201
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:6977
bool unmarkWeightsRefittable(char const *name) noexcept
Unmark weights as refittable when the builder flag kREFIT_INDIVIDUAL is set.
Definition: NvInfer.h:7817
bool markWeightsRefittable(char const *name) noexcept
Mark weights as refittable when the builder flag kREFIT_INDIVIDUAL is set.
Definition: NvInfer.h:7805
IDeconvolutionLayer * addDeconvolutionNd(ITensor &input, int64_t nbOutputMaps, Dims kernelSize, Weights kernelWeights, Weights biasWeights) noexcept
Add a multi-dimension deconvolution layer to the network.
Definition: NvInfer.h:7334
IResizeLayer * addResize(ITensor &input) noexcept
Add a resize layer to the network.
Definition: NvInfer.h:7388
IUnsqueezeLayer * addUnsqueeze(ITensor &input, ITensor &axes) noexcept
Add an unsqueeze layer to the network.
Definition: NvInfer.h:7870
IMatrixMultiplyLayer * addMatrixMultiply(ITensor &input0, MatrixOperation op0, ITensor &input1, MatrixOperation op1) noexcept
Add a MatrixMultiply layer to the network.
Definition: NvInfer.h:7033
ISoftMaxLayer * addSoftMax(ITensor &input) noexcept
Add a SoftMax layer to the network.
Definition: NvInfer.h:6721
bool isDebugTensor(nvinfer1::ITensor const &tensor) const noexcept
Check if a tensor is marked as debug tensor.
Definition: NvInfer.h:6607
bool unmarkDebug(ITensor &tensor) noexcept
Unmark a tensor as a debug tensor.
Definition: NvInfer.h:6597
IEinsumLayer * addEinsum(ITensor *const *inputs, int32_t nbInputs, char const *equation) noexcept
Add an Einsum layer to the network.
Definition: NvInfer.h:7680
void markOutput(ITensor &tensor) noexcept
Mark a tensor as a network output.
Definition: NvInfer.h:6563
IPaddingLayer * addPaddingNd(ITensor &input, Dims const &prePadding, Dims const &postPadding) noexcept
Add a padding layer to the network. Only 2D padding is currently supported.
Definition: NvInfer.h:7515
INonZeroLayer * addNonZero(ITensor &input) noexcept
Add a nonzero layer to the network.
Definition: NvInfer.h:7048
int32_t getNbOutputs() const noexcept
Get the number of outputs in the network.
Definition: NvInfer.h:6886
bool setWeightsName(Weights weights, char const *name) noexcept
Associate a name with all current uses of the given weights.
Definition: NvInfer.h:7539
bool unmarkUnfusedTensorsAsDebugTensors() noexcept
Undo the marking of unfused tensors as debug tensors.
Definition: NvInfer.h:6643
Forward declaration of IEngineInspector for use by other interfaces.
Definition: NvInferRuntime.h:51
Definition: NvInfer.h:3598
virtual ~INonZeroLayer() noexcept=default
A normalization layer in a network definition.
Definition: NvInfer.h:6175
float getEpsilon() const noexcept
Get the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6194
uint32_t getAxes() const noexcept
Get the axes value used for the normalization calculation.
Definition: NvInfer.h:6214
virtual ~INormalizationLayer() noexcept=default
void setEpsilon(float eps) noexcept
Set the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6184
DataType getComputePrecision() const noexcept
Get the compute precision of this layer.
Definition: NvInfer.h:6281
apiv::VNormalizationLayer * mImpl
Definition: NvInfer.h:6287
int64_t getNbGroups() const noexcept
Get the number of groups used to split the channels for the normalization calculation.
Definition: NvInfer.h:6245
void setAxes(uint32_t axesMask) noexcept
Set the reduction axes for the normalization calculation.
Definition: NvInfer.h:6204
void setComputePrecision(DataType type) noexcept
Set the compute precision of this layer.
Definition: NvInfer.h:6271
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups used to split the channels in the normalization calculation.
Definition: NvInfer.h:6235
A OneHot layer in a network definition.
Definition: NvInfer.h:5828
virtual ~IOneHotLayer() noexcept=default
apiv::VOneHotLayer * mImpl
Definition: NvInfer.h:5849
void setAxis(int32_t axis) noexcept
Set the axis parameter.
Definition: NvInfer.h:5835
int32_t getAxis() const noexcept
Get the value of the axis parameter.
Definition: NvInfer.h:5843
Optimization profile for dynamic input dimensions and shape tensors.
Definition: NvInferRuntime.h:2041
Layer that represents a padding operation.
Definition: NvInfer.h:2822
Dims getPostPaddingNd() const noexcept
Get the padding that is applied at the end of the tensor.
Definition: NvInfer.h:2871
void setPrePaddingNd(Dims const &padding) noexcept
Set the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2833
virtual ~IPaddingLayer() noexcept=default
void setPostPaddingNd(Dims const &padding) noexcept
Set the padding that is applied at the end of the tensor.
Definition: NvInfer.h:2859
Dims getPrePaddingNd() const noexcept
Get the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2845
apiv::VPaddingLayer * mImpl
Definition: NvInfer.h:2877
Layer that represents a parametric ReLU operation.
Definition: NvInfer.h:3785
apiv::VParametricReLULayer * mImpl
Definition: NvInfer.h:3787
virtual ~IParametricReLULayer() noexcept=default
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferRuntimeCommon.h:56
A Pooling layer in a network definition.
Definition: NvInfer.h:1377
PoolingType getPoolingType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1396
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1529
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:1505
bool getAverageCountExcludesPadding() const noexcept
Get whether average pooling uses as a denominator the overlap area between the window and the unpadde...
Definition: NvInfer.h:1449
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1477
void setPoolingType(PoolingType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1386
void setWindowSizeNd(Dims const &windowSize) noexcept
Set the multi-dimension window size for pooling.
Definition: NvInfer.h:1542
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1518
Dims getWindowSizeNd() const noexcept
Get the multi-dimension window size for pooling.
Definition: NvInfer.h:1552
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:1438
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding for pooling.
Definition: NvInfer.h:1596
float getBlendFactor() const noexcept
Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1424
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride for pooling.
Definition: NvInfer.h:1567
Dims getStrideNd() const noexcept
Get the multi-dimension stride for pooling.
Definition: NvInfer.h:1577
virtual ~IPoolingLayer() noexcept=default
Dims getPaddingNd() const noexcept
Get the multi-dimension padding for pooling.
Definition: NvInfer.h:1608
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding for pooling.
Definition: NvInfer.h:1495
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding for pooling.
Definition: NvInfer.h:1467
void setBlendFactor(float blendFactor) noexcept
Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1411
A Quantize layer in a network definition.
Definition: NvInfer.h:5278
void setToType(DataType toType) noexcept
Set the Quantize layer output type.
Definition: NvInfer.h:5315
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5299
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5288
virtual ~IQuantizeLayer() noexcept=default
DataType getToType() const noexcept
Return the Quantize layer output type.
Definition: NvInfer.h:5327
A RaggedSoftmax layer in a network definition.
Definition: NvInfer.h:3619
apiv::VRaggedSoftMaxLayer * mImpl
Definition: NvInfer.h:3621
virtual ~IRaggedSoftMaxLayer() noexcept=default
A recurrence layer in a network definition.
Definition: NvInfer.h:4491
virtual ~IRecurrenceLayer() noexcept=default
Layer that represents a reduction across a non-bool tensor.
Definition: NvInfer.h:2742
void setKeepDimensions(bool keepDimensions) noexcept
Set the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2789
void setOperation(ReduceOperation op) noexcept
Set the reduce operation for the layer.
Definition: NvInfer.h:2749
ReduceOperation getOperation() const noexcept
Get the reduce operation for the layer.
Definition: NvInfer.h:2759
virtual ~IReduceLayer() noexcept=default
uint32_t getReduceAxes() const noexcept
Get the axes over which to reduce for the layer.
Definition: NvInfer.h:2779
void setReduceAxes(uint32_t reduceAxes) noexcept
Set the axes over which to reduce.
Definition: NvInfer.h:2769
apiv::VReduceLayer * mImpl
Definition: NvInfer.h:2805
bool getKeepDimensions() const noexcept
Get the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2799
A resize layer in a network definition.
Definition: NvInfer.h:3974
void setSelectorForSinglePixel(ResizeSelector selector) noexcept
Set coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4135
void setNearestRounding(ResizeRoundMode value) noexcept
Set rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4159
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:4053
void setOutputDimensions(Dims const &dimensions) noexcept
Set the output dimensions.
Definition: NvInfer.h:3994
void setCubicCoeff(float A) noexcept
Set the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4191
void setScales(float const *scales, int32_t nbScales) noexcept
Set the resize scales.
Definition: NvInfer.h:4034
float getCubicCoeff() const noexcept
Get the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4201
ResizeSelector getSelectorForSinglePixel() const noexcept
Get the coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4145
InterpolationMode getResizeMode() const noexcept
Get resize mode for an input tensor.
Definition: NvInfer.h:4075
void setCoordinateTransformation(ResizeCoordinateTransformation coordTransform) noexcept
Set coordinate transformation function.
Definition: NvInfer.h:4110
void setExcludeOutside(bool excludeFlag) noexcept
Set the state for excluding outside pixels.
Definition: NvInfer.h:4214
void setResizeMode(InterpolationMode interpolationMode) noexcept
Set resize mode for an input tensor.
Definition: NvInfer.h:4065
Dims getOutputDimensions() const noexcept
Get the output dimensions.
Definition: NvInfer.h:4004
ResizeRoundMode getNearestRounding() const noexcept
Get rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4169
bool getExcludeOutside() const noexcept
Get the state for excluding outside pixels.
Definition: NvInfer.h:4224
ResizeCoordinateTransformation getCoordinateTransformation() const noexcept
Get coordinate transformation function.
Definition: NvInfer.h:4120
A ReverseSequence layer in a network definition.
Definition: NvInfer.h:6103
void setSequenceAxis(int32_t sequenceAxis) noexcept
Set the sequence axis. Default is 0.
Definition: NvInfer.h:6136
int32_t getBatchAxis() const noexcept
Return the batch axis. Return 1 if no batch axis was set.
Definition: NvInfer.h:6123
apiv::VReverseSequenceLayer * mImpl
Definition: NvInfer.h:6152
int32_t getSequenceAxis() const noexcept
Return the sequence axis. Return 0 if no sequence axis was set.
Definition: NvInfer.h:6146
void setBatchAxis(int32_t batchAxis) noexcept
Set the batch axis. Default is 1.
Definition: NvInfer.h:6113
virtual ~IReverseSequenceLayer() noexcept=default
A Scale layer in a network definition.
Definition: NvInfer.h:1774
Weights getScale() const noexcept
Get the scale value.
Definition: NvInfer.h:1831
Weights getPower() const noexcept
Get the power value.
Definition: NvInfer.h:1851
void setScale(Weights scale) noexcept
Set the scale value.
Definition: NvInfer.h:1821
void setPower(Weights power) noexcept
Set the power value.
Definition: NvInfer.h:1841
ScaleMode getMode() const noexcept
Get the scale mode.
Definition: NvInfer.h:1791
void setShift(Weights shift) noexcept
Set the shift value.
Definition: NvInfer.h:1801
void setChannelAxis(int32_t channelAxis) noexcept
Set the channel axis.
Definition: NvInfer.h:1887
Weights getShift() const noexcept
Get the shift value.
Definition: NvInfer.h:1811
virtual ~IScaleLayer() noexcept=default
void setMode(ScaleMode mode) noexcept
Set the scale mode.
Definition: NvInfer.h:1781
int32_t getChannelAxis() const noexcept
Get the channel axis.
Definition: NvInfer.h:1866
A scatter layer in a network definition. Supports several kinds of scattering.
Definition: NvInfer.h:5756
void setMode(ScatterMode mode) noexcept
Set the scatter mode.
Definition: NvInfer.h:5763
apiv::VScatterLayer * mImpl
Definition: NvInfer.h:5797
void setAxis(int32_t axis) noexcept
Set the axis used by ScatterMode::kELEMENTS.
Definition: NvInfer.h:5783
int32_t getAxis() const noexcept
Get the axis.
Definition: NvInfer.h:5791
ScatterMode getMode() const noexcept
Get the scatter mode.
Definition: NvInfer.h:5773
virtual ~IScatterLayer() noexcept=default
Select elements from two data tensors based on a condition tensor.
Definition: NvInfer.h:4799
virtual ~ISelectLayer() noexcept=default
Layer type for getting shape of a tensor.
Definition: NvInfer.h:3347
virtual ~IShapeLayer() noexcept=default
apiv::VShapeLayer * mImpl
Definition: NvInfer.h:3349
Layer type for shuffling data.
Definition: NvInfer.h:2910
apiv::VShuffleLayer * mImpl
Definition: NvInfer.h:3068
void setFirstTranspose(Permutation permutation) noexcept
Set the permutation applied by the first transpose operation.
Definition: NvInfer.h:2921
void setSecondTranspose(Permutation permutation) noexcept
Set the permutation applied by the second transpose operation.
Definition: NvInfer.h:3021
Dims getReshapeDimensions() const noexcept
Get the reshaped dimensions.
Definition: NvInfer.h:2974
void setReshapeDimensions(Dims const &dimensions) noexcept
Set the reshaped dimensions.
Definition: NvInfer.h:2961
Permutation getFirstTranspose() const noexcept
Get the permutation applied by the first transpose operation.
Definition: NvInfer.h:2933
virtual ~IShuffleLayer() noexcept=default
Permutation getSecondTranspose() const noexcept
Get the permutation applied by the second transpose operation.
Definition: NvInfer.h:3033
bool getZeroIsPlaceholder() const noexcept
Get meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3062
void setZeroIsPlaceholder(bool zeroIsPlaceholder) noexcept
Set meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3049
Slices an input tensor into an output tensor based on the offset and strides.
Definition: NvInfer.h:3162
void setStride(Dims const &stride) noexcept
Set the stride for computing the output slice data.
Definition: NvInfer.h:3231
apiv::VSliceLayer * mImpl
Definition: NvInfer.h:3330
virtual ~ISliceLayer() noexcept=default
void setSize(Dims const &size) noexcept
Set the dimensions of the output slice.
Definition: NvInfer.h:3202
void setAxes(Dims const &axes) noexcept
Set the axes for this ISliceLayer.
Definition: NvInfer.h:3309
void setStart(Dims const &start) noexcept
Set the start offset that the slice layer uses to create the output slice.
Definition: NvInfer.h:3173
Dims getStart() const noexcept
Get the start offset for the slice layer.
Definition: NvInfer.h:3188
void setMode(SampleMode mode) noexcept
Set the slice mode.
Definition: NvInfer.h:3256
Dims getSize() const noexcept
Get dimensions of the output slice.
Definition: NvInfer.h:3217
SampleMode getMode() const noexcept
Get the slice mode.
Definition: NvInfer.h:3266
Dims getStride() const noexcept
Get the stride for the output slice.
Definition: NvInfer.h:3246
Dims getAxes() const noexcept
Get the axes for this ISliceLayer.
Definition: NvInfer.h:3324
A Softmax layer in a network definition.
Definition: NvInfer.h:1918
void setAxes(uint32_t axes) noexcept
Set the axis along which softmax is computed. Currently, only one axis can be set.
Definition: NvInfer.h:1940
uint32_t getAxes() const noexcept
Get the axis along which softmax occurs.
Definition: NvInfer.h:1950
virtual ~ISoftMaxLayer() noexcept=default
Layer that represents a squeeze operation, removing unit dimensions of the input tensor on a set of a...
Definition: NvInfer.h:6301
virtual ~ISqueezeLayer() noexcept=default
apiv::VSqueezeLayer * mImpl
Definition: NvInfer.h:6318
A tensor in a network definition.
Definition: NvInfer.h:183
void setAllowedFormats(TensorFormats formats) noexcept
Set allowed formats for an input or output tensor. By default all formats are allowed....
Definition: NvInfer.h:334
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions of a tensor.
Definition: NvInfer.h:231
void setName(char const *name) noexcept
Set the tensor name.
Definition: NvInfer.h:200
bool isExecutionTensor() const noexcept
Whether the tensor is an execution tensor.
Definition: NvInfer.h:399
char const * getName() const noexcept
Get the tensor name.
Definition: NvInfer.h:212
bool isShapeTensor() const noexcept
Whether the tensor is a shape tensor.
Definition: NvInfer.h:378
bool isNetworkInput() const noexcept
Whether the tensor is a network input.
Definition: NvInfer.h:304
TRT_DEPRECATED void setType(DataType type) noexcept
Set the data type of a tensor.
Definition: NvInfer.h:281
bool isNetworkOutput() const noexcept
Whether the tensor is a network output.
Definition: NvInfer.h:312
DataType getType() const noexcept
Get the data type of a tensor.
Definition: NvInfer.h:296
apiv::VTensor * mImpl
Definition: NvInfer.h:446
virtual ~ITensor() noexcept=default
void setDimensionName(int32_t index, char const *name) noexcept
Name a dimension of an input tensor.
Definition: NvInfer.h:425
char const * getDimensionName(int32_t index) const noexcept
Get the name of an input dimension.
Definition: NvInfer.h:440
Dims getDimensions() const noexcept
Get the dimensions of a tensor.
Definition: NvInfer.h:245
TensorFormats getAllowedFormats() const noexcept
Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor,...
Definition: NvInfer.h:347
Class to handle tactic timing info collected from builder.
Definition: NvInfer.h:8175
int64_t queryKeys(TimingCacheKey *keyBuffer, int64_t capacity) const noexcept
Query cache keys from Timing Cache.
Definition: NvInfer.h:8241
bool combine(ITimingCache const &inputCache, bool ignoreMismatch) noexcept
Combine input timing cache into local instance.
Definition: NvInfer.h:8212
TimingCacheValue query(TimingCacheKey const &key) const noexcept
Query value in a cache entry.
Definition: NvInfer.h:8258
virtual ~ITimingCache() noexcept=default
bool update(TimingCacheKey const &key, TimingCacheValue const &value) noexcept
Update values in a cache entry.
Definition: NvInfer.h:8280
apiv::VTimingCache * mImpl
Definition: NvInfer.h:8286
bool reset() noexcept
Empty the timing cache.
Definition: NvInfer.h:8222
Layer that represents a TopK reduction.
Definition: NvInfer.h:3387
void setK(int32_t k) noexcept
Set the static k value for the layer.
Definition: NvInfer.h:3418
void setReduceAxes(uint32_t reduceAxes) noexcept
Set which axes to reduce for the layer.
Definition: NvInfer.h:3442
TopKOperation getOperation() const noexcept
Get the operation for the layer.
Definition: NvInfer.h:3404
apiv::VTopKLayer * mImpl
Definition: NvInfer.h:3474
void setOperation(TopKOperation op) noexcept
Set the operation for the layer.
Definition: NvInfer.h:3394
int32_t getK() const noexcept
Get the k value for the layer.
Definition: NvInfer.h:3432
uint32_t getReduceAxes() const noexcept
Get the axes to reduce for the layer.
Definition: NvInfer.h:3452
virtual ~ITopKLayer() noexcept=default
A layer that represents a trip-count limiter.
Definition: NvInfer.h:4612
TripLimit getTripLimit() const noexcept
Get a trip limiter type.
Definition: NvInfer.h:4617
virtual ~ITripLimitLayer() noexcept=default
Layer that represents an unary operation.
Definition: NvInfer.h:2667
void setOperation(UnaryOperation op) noexcept
Set the unary operation for the layer.
Definition: NvInfer.h:2676
apiv::VUnaryLayer * mImpl
Definition: NvInfer.h:2692
UnaryOperation getOperation() const noexcept
Get the unary operation for the layer.
Definition: NvInfer.h:2686
virtual ~IUnaryLayer() noexcept=default
Layer that represents an unsqueeze operation, which reshapes the input tensor by inserting unit-lengt...
Definition: NvInfer.h:6330
virtual ~IUnsqueezeLayer() noexcept=default
apiv::VUnsqueezeLayer * mImpl
Definition: NvInfer.h:6347
An Interface class for version control.
Definition: NvInferRuntimeBase.h:276
Version information associated with a TRT interface.
Definition: NvInferRuntimeBase.h:241
An array of weights used as a layer parameter.
Definition: NvInferRuntime.h:124
Definition: NvInferRuntimeBase.h:413
Definition: NvInferRuntime.h:1120
Definition: NvInfer.h:8524
virtual bool stepComplete(char const *phaseName, int32_t step) noexcept=0
Signal that a step of an optimizer phase has finished.
virtual ~IProgressMonitor() noexcept=default
IProgressMonitor()=default
virtual void phaseFinish(char const *phaseName) noexcept=0
Signal that a phase of the optimizer has finished.
virtual void phaseStart(char const *phaseName, char const *parentPhase, int32_t nbSteps) noexcept=0
Signal that a phase of the optimizer has started.
IBuilder * createInferBuilder(ILogger &logger) noexcept
Create an instance of an IBuilder class.
Definition: NvInfer.h:9759
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:2327
ResizeSelector
The coordinate selector when resize to single pixel output.
Definition: NvInfer.h:3879
@ kFORMULA
Use formula to map the original index.
@ kUPPER
Select the upper left pixel.
EngineCapability
List of supported engine capability flows.
Definition: NvInferRuntime.h:76
nvinfer1::IPluginRegistry * getBuilderPluginRegistry(nvinfer1::EngineCapability capability) noexcept
Return the plugin registry for building a Standard engine, or nullptr if no registry exists.
MemoryPoolType
The type for memory pools used by TensorRT.
Definition: NvInfer.h:8297
ScaleMode
Controls how shift, scale and power are applied in a Scale layer.
Definition: NvInfer.h:1731
@ kUNIFORM
Identical coefficients across all elements of the tensor.
@ kCHANNEL
Per-channel coefficients.
RuntimePlatform
Describes the intended runtime platform (operating system and CPU architecture) for the execution of ...
Definition: NvInfer.h:7897
HardwareCompatibilityLevel
Describes requirements of compatibility with GPU architectures other than that of the GPU on which th...
Definition: NvInfer.h:8416
@ kSAME_COMPUTE_CAPABILITY
CumulativeOperation
Enumerates the cumulative operations that may be performed by a Cumulative layer.
Definition: NvInfer.h:6363
BoundingBoxFormat
Representation of bounding box data used for the Boxes input tensor in INMSLayer.
Definition: NvInfer.h:5948
@ 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:8119
constexpr int32_t EnumMax< LayerType >() noexcept
Definition: NvInfer.h:118
ComputeCapability
Describes compute capability that an engine will be built for.
Definition: NvInfer.h:8465
@ kSM120
Target NVIDIA Blackwell GPU architecture (SM 12.0).
@ kSM75
Target NVIDIA Turing GPU architecture (SM 7.5).
@ kSM80
Target NVIDIA Ampere GPU architecture (SM 8.0).
@ kCURRENT
Use the compute capability of the current GPU in the environment.
@ kSM89
Target NVIDIA Ada Lovelace GPU architecture (SM 8.9).
@ kSM86
Target NVIDIA Ampere GPU architecture (SM 8.6).
UnaryOperation
Enumerates the unary operations that may be performed by a Unary layer.
Definition: NvInfer.h:2620
@ kISINF
Return true if input value equals +/- infinity for floating-point data type.
@ kCOSH
Hyperbolic cosine.
@ kACOSH
Inverse hyperbolic cosine.
@ kERF
Gauss error function.
@ kISNAN
Return true if input value is a NaN for floating-point data type.
@ kROUND
Round to nearest even for floating-point data type.
@ kATANH
Inverse hyperbolic tangent.
@ kASINH
Inverse hyperbolic sine.
@ kSIGN
Sign, If input > 0, output 1; if input < 0, output -1; if input == 0, output 0.
constexpr int32_t EnumMax< ReduceOperation >() noexcept
Definition: NvInfer.h:2729
constexpr int32_t EnumMax< TripLimit >() noexcept
Definition: NvInfer.h:4280
ActivationType
Enumerates the types of activation to perform in an activation layer.
Definition: NvInfer.h:137
@ kSELU
Selu activation: x>0 ? beta * x : beta * (alpha*exp(x) - alpha)
@ kSCALED_TANH
Scaled tanh activation: alpha*tanh(beta*x)
@ kRELU
Rectified linear activation.
@ kELU
Elu activation: x>=0 ? x : alpha * (exp(x) - 1).
@ kLEAKY_RELU
LeakyRelu activation: x>=0 ? x : alpha * x.
@ kSOFTSIGN
Softsign activation: x / (1+|x|)
@ kHARD_SIGMOID
Hard sigmoid activation: max(0, min(1, alpha*x+beta))
@ kTHRESHOLDED_RELU
Thresholded ReLU activation: x>alpha ? x : 0.
@ kSIGMOID
Sigmoid activation.
@ kCLIP
Clip activation: max(alpha, min(beta, x))
@ kGELU_TANH
GELU tanh activation: 0.5 * x * (1 + tanh(sqrt(2/pi) * (0.044715F * pow(x, 3) + x)))
@ kGELU_ERF
GELU erf activation: 0.5 * x * (1 + erf(sqrt(0.5) * x))
@ kSOFTPLUS
Parametric softplus activation: alpha*log(exp(beta*x)+1)
FillOperation
Enumerates the tensor fill operations that may performed by a fill layer.
Definition: NvInfer.h:4860
@ kRANDOM_UNIFORM
Randomly draw values from a uniform distribution.
@ kRANDOM_NORMAL
Randomly draw values from a normal distribution.
ResizeRoundMode
The rounding mode for nearest neighbor resize.
Definition: NvInfer.h:3909
@ kHALF_DOWN
Round half down.
nvinfer1::safe::IPluginRegistry * getBuilderSafePluginRegistry(nvinfer1::EngineCapability capability) noexcept
Return the plugin registry for building a Safety engine, or nullptr if no registry exists.
PaddingMode
Enumerates the modes of padding to perform in convolution, deconvolution and pooling layer,...
Definition: NvInfer.h:909
@ kSAME_LOWER
Use SAME padding, with prePadding >= postPadding.
@ kEXPLICIT_ROUND_DOWN
Use explicit padding, rounding output size down.
@ kEXPLICIT_ROUND_UP
Use explicit padding, rounding output size up.
@ kSAME_UPPER
Use SAME padding, with prePadding <= postPadding.
TripLimit
Enum that describes kinds of trip limits.
Definition: NvInfer.h:4268
@ kWHILE
Tensor is a scalar of type kBOOL. Loop terminates when value is false.
@ kCOUNT
Tensor is a scalar of type kINT32 or kINT64 that contains the trip count.
uint32_t NetworkDefinitionCreationFlags
Represents one or more NetworkDefinitionCreationFlag flags using binary OR operations....
Definition: NvInfer.h:9462
PreviewFeature
Define preview features.
Definition: NvInfer.h:8372
@ kRUNTIME_ACTIVATION_RESIZE_10_10
@ kALIASED_PLUGIN_IO_10_03
TilingOptimizationLevel
Define the optimization levels for Tiling.
Definition: NvInfer.h:8491
@ kFAST
Use a fast algorithm and heuristic based strategy. Slightly increases engine build time.
@ kFULL
Increase search space even wider. Significantly increases engine build time.
constexpr int32_t EnumMax< GatherMode >() noexcept
Definition: NvInfer.h:2435
DataType
The type of weights and tensors.
Definition: NvInferRuntimeBase.h:143
uint32_t BuilderFlags
Represents one or more BuilderFlag values using binary OR operations, e.g., 1U << BuilderFlag::kFP16 ...
Definition: NvInfer.h:7927
DeviceType
The device that this layer/network will execute on.
Definition: NvInferRuntime.h:814
constexpr int32_t EnumMax< ScaleMode >() noexcept
Definition: NvInfer.h:1743
LayerType
The type values of layer classes.
Definition: NvInfer.h:58
@ kGRID_SAMPLE
Grid sample layer.
@ kRAGGED_SOFTMAX
Ragged softmax layer.
@ kDECONVOLUTION
Deconvolution layer.
@ kASSERTION
Assertion layer.
@ kMATRIX_MULTIPLY
Matrix multiply layer.
@ kCONDITION
Condition layer.
@ kCUMULATIVE
Cumulative layer.
@ kCONDITIONAL_INPUT
Conditional Input layer.
@ kIDENTITY
Identity layer.
@ kNORMALIZATION
Normalization layer.
@ kQUANTIZE
Quantize layer.
@ kCONVOLUTION
Convolution layer.
@ kPARAMETRIC_RELU
Parametric ReLU layer.
@ kUNSQUEEZE
Unsqueeze Layer.
@ kCONCATENATION
Concatenation layer.
@ kREVERSE_SEQUENCE
Reverse sequence layer.
@ kRECURRENCE
Loop Recurrence layer.
@ kDEQUANTIZE
Dequantize layer.
@ kPLUGIN_V3
PluginV3 layer.
@ kITERATOR
Loop Iterator layer.
@ kTRIP_LIMIT
Loop Trip limit layer.
@ kDYNAMIC_QUANTIZE
Dynamic Quantize layer.
@ kUNARY
UnaryOp operation Layer.
@ kACTIVATION
Activation layer.
@ kELEMENTWISE
Elementwise layer.
@ kPLUGIN_V2
PluginV2 layer.
@ kLOOP_OUTPUT
Loop output layer.
@ kCONDITIONAL_OUTPUT
Conditional Output layer.
@ kCONSTANT
Constant layer.
@ kNON_ZERO
NonZero layer.
SampleMode
Controls how ISliceLayer and IGridSample handle out-of-bounds coordinates.
Definition: NvInfer.h:3078
@ kCLAMP
Out of bounds indices are clamped to bounds.
@ kSTRICT_BOUNDS
Fail with error when the coordinates are out of bounds.
@ kWRAP
Coordinates wrap around periodically.
GatherMode
Control form of IGatherLayer.
Definition: NvInfer.h:2423
@ kDEFAULT
Similar to ONNX Gather.
@ kELEMENT
Similar to ONNX GatherElements.
@ kND
Similar to ONNX GatherND.
uint32_t TensorFormats
It is capable of representing one or more TensorFormat by binary OR operations, e....
Definition: NvInfer.h:129
ProfilingVerbosity
List of verbosity levels of layer information exposed in NVTX annotations and in IEngineInspector.
Definition: NvInferRuntime.h:2339
NetworkDefinitionCreationFlag
List of immutable network properties expressed at network creation time. NetworkDefinitionCreationFla...
Definition: NvInfer.h:9473
ElementWiseOperation
Enumerates the binary operations that may be performed by an ElementWise layer.
Definition: NvInfer.h:2333
@ kSUB
Subtract the second element from the first.
@ kSUM
Sum of the two elements.
@ kPROD
Product of the two elements.
@ kFLOOR_DIV
Floor division of the first element by the second.
@ kEQUAL
Check if two elements are equal.
@ kAND
Logical AND of two elements.
@ kOR
Logical OR of two elements.
@ kMIN
Minimum of the two elements.
@ kPOW
The first element to the power of the second element.
@ kLESS
Check if element in first tensor is less than corresponding element in second tensor.
@ kGREATER
Check if element in first tensor is greater than corresponding element in second tensor.
@ kXOR
Logical XOR of two elements.
@ kDIV
Divide the first element by the second.
constexpr int32_t EnumMax< SampleMode >() noexcept
Definition: NvInfer.h:3094
InterpolationMode
Enumerates various modes of interpolation.
Definition: NvInfer.h:3797
@ kNEAREST
ND (0 < N <= 8) nearest neighbor resizing.
@ kCUBIC
Supports bicubic (2D) interpolation.
@ kLINEAR
Supports linear (1D), bilinear (2D), and trilinear (3D) interpolation.
BuilderFlag
List of valid modes that the builder can enable when creating an engine from a network definition.
Definition: NvInfer.h:7937
@ kWEIGHT_STREAMING
Enable weight streaming for the current engine.
@ kDEBUG
Enable debugging of layers via synchronizing after every layer.
@ kGPU_FALLBACK
Enable layers marked to execute on GPU if layer cannot execute on DLA.
@ kSPARSE_WEIGHTS
Allow the builder to examine weights and use optimized functions when weights have suitable sparsity.
@ kERROR_ON_TIMING_CACHE_MISS
@ kEDITABLE_TIMING_CACHE
Enable editable timing cache.
@ kPREFER_PRECISION_CONSTRAINTS
@ kDISTRIBUTIVE_INDEPENDENCE
@ kSTRIP_PLAN
Strip the refittable weights from the engine plan file.
@ kMONITOR_MEMORY
Enable memory monitor during build time.
@ kDISABLE_TIMING_CACHE
Disable reuse of timing information across identical layers.
@ kDISABLE_COMPILATION_CACHE
@ kREFIT
Enable building a refittable engine.
@ kOBEY_PRECISION_CONSTRAINTS
@ kREJECT_EMPTY_ALGORITHMS
constexpr int32_t EnumMax< TopKOperation >() noexcept
Definition: NvInfer.h:3370
constexpr int32_t EnumMax< MemoryPoolType >() noexcept
Definition: NvInfer.h:8358
TopKOperation
Enumerates the operations that may be performed by a TopK layer.
Definition: NvInfer.h:3359
ReduceOperation
Enumerates the reduce operations that may be performed by a Reduce layer.
Definition: NvInfer.h:2715
constexpr int32_t EnumMax< LoopOutput >() noexcept
Definition: NvInfer.h:4257
constexpr int32_t EnumMax< NetworkDefinitionCreationFlag >() noexcept
Definition: NvInfer.h:9492
ScatterMode
Control form of IScatterLayer.
Definition: NvInfer.h:5682
MatrixOperation
Enumerates the operations that may be performed on a tensor by IMatrixMultiplyLayer before multiplica...
Definition: NvInfer.h:3485
@ kTRANSPOSE
Like kNONE, but transpose the matrix dimensions.
ResizeCoordinateTransformation
The resize coordinate transformation function.
Definition: NvInfer.h:3825
constexpr int32_t EnumMax< UnaryOperation >() noexcept
Definition: NvInfer.h:2654
LoopOutput
Enum that describes kinds of loop outputs.
Definition: NvInfer.h:4240
@ kLAST_VALUE
Output value is value of tensor for last iteration.
@ kCONCATENATE
Output value is concatenation of values of tensor for each iteration, in forward order.
@ kREVERSE
Output value is concatenation of values of tensor for each iteration, in reverse order.
constexpr int32_t EnumMax< BoundingBoxFormat >() noexcept
Definition: NvInfer.h:5961
constexpr int32_t EnumMax< MatrixOperation >() noexcept
Definition: NvInfer.h:3513
PoolingType
The type of pooling to perform in a pooling layer.
Definition: NvInfer.h:1345
@ kAVERAGE
Average over elements. If the tensor is padded, the count includes the padding.
@ kMAX
Maximum over elements.
@ kMAX_AVERAGE_BLEND
Blending between max and average pooling: (1-blendFactor)*maxPool + blendFactor*avgPool.
v_1_0::IProgressMonitor IProgressMonitor
Definition: NvInfer.h:8607
constexpr int32_t EnumMax< FillOperation >() noexcept
Definition: NvInfer.h:4891
constexpr int32_t EnumMax< ScatterMode >() noexcept
Definition: NvInfer.h:5693
Represents a permutation of dimensions.
Definition: NvInfer.h:2887
Declaration of EnumMaxImpl struct to store maximum number of elements in an enumeration type.
Definition: NvInferRuntimeBase.h:128
The key to retrieve timing cache entries.
Definition: NvInfer.h:8139
Definition: NvInfer.h:8151
uint64_t tacticHash
Hash of the selected tactic.
Definition: NvInfer.h:8153
float timingMSec
Timing of this tactic in milliseconds. Negative numbers and NaN are invalid values.
Definition: NvInfer.h:8155