160 static constexpr int32_t kVALUE = 14;
199 mImpl->setName(name);
211 return mImpl->getName();
230 mImpl->setDimensions(dimensions);
244 return mImpl->getDimensions();
259 mImpl->setType(type);
271 return mImpl->getType();
286 return mImpl->setDynamicRange(min, max);
294 return mImpl->isNetworkInput();
302 return mImpl->isNetworkOutput();
319 mImpl->setBroadcastAcrossBatch(broadcastAcrossBatch);
333 return mImpl->getBroadcastAcrossBatch();
345 return mImpl->getLocation();
364 mImpl->setLocation(location);
374 return mImpl->dynamicRangeIsSet();
382 mImpl->resetDynamicRange();
392 return mImpl->getDynamicRangeMin();
402 return mImpl->getDynamicRangeMax();
422 mImpl->setAllowedFormats(formats);
435 return mImpl->getAllowedFormats();
466 return mImpl->isShapeTensor();
487 return mImpl->isExecutionTensor();
513 mImpl->setDimensionName(index, name);
528 return mImpl->getDimensionName(index);
553 return mLayer->getType();
567 mLayer->setName(name);
577 return mLayer->getName();
585 return mLayer->getNbInputs();
598 return mLayer->getInput(index);
606 return mLayer->getNbOutputs();
616 return mLayer->getOutput(index);
633 return mLayer->setInput(index, tensor);
665 mLayer->setPrecision(dataType);
677 return mLayer->getPrecision();
689 return mLayer->precisionIsSet();
699 mLayer->resetPrecision();
746 mLayer->setOutputType(index, dataType);
761 return mLayer->getOutputType(index);
775 return mLayer->outputTypeIsSet(index);
787 return mLayer->resetOutputType(index);
805 mLayer->setMetadata(metadata);
818 return mLayer->getMetadata();
823 apiv::VLayer* mLayer;
1000 static constexpr int32_t kVALUE = 4;
1028 mImpl->setNbOutputMaps(nbOutputMaps);
1038 return mImpl->getNbOutputMaps();
1058 mImpl->setNbGroups(nbGroups);
1068 return mImpl->getNbGroups();
1082 mImpl->setKernelWeights(weights);
1092 return mImpl->getKernelWeights();
1107 mImpl->setBiasWeights(weights);
1117 return mImpl->getBiasWeights();
1134 mImpl->setPrePadding(padding);
1144 return mImpl->getPrePadding();
1161 mImpl->setPostPadding(padding);
1171 return mImpl->getPostPadding();
1185 mImpl->setPaddingMode(paddingMode);
1197 return mImpl->getPaddingMode();
1210 mImpl->setKernelSizeNd(kernelSize);
1220 return mImpl->getKernelSizeNd();
1235 mImpl->setStrideNd(stride);
1245 return mImpl->getStrideNd();
1263 mImpl->setPaddingNd(padding);
1275 return mImpl->getPaddingNd();
1289 mImpl->setDilationNd(dilation);
1299 return mImpl->getDilationNd();
1348 mImpl->setActivationType(type);
1358 return mImpl->getActivationType();
1373 mImpl->setAlpha(alpha);
1387 mImpl->setBeta(beta);
1396 return mImpl->getAlpha();
1405 return mImpl->getBeta();
1435 static constexpr int32_t kVALUE = 3;
1462 mImpl->setPoolingType(type);
1472 return mImpl->getPoolingType();
1487 mImpl->setBlendFactor(blendFactor);
1500 return mImpl->getBlendFactor();
1514 mImpl->setAverageCountExcludesPadding(exclusive);
1525 return mImpl->getAverageCountExcludesPadding();
1543 mImpl->setPrePadding(padding);
1553 return mImpl->getPrePadding();
1571 mImpl->setPostPadding(padding);
1581 return mImpl->getPostPadding();
1594 mImpl->setPaddingMode(paddingMode);
1605 return mImpl->getPaddingMode();
1618 mImpl->setWindowSizeNd(windowSize);
1628 return mImpl->getWindowSizeNd();
1643 mImpl->setStrideNd(stride);
1653 return mImpl->getStrideNd();
1672 mImpl->setPaddingNd(padding);
1684 return mImpl->getPaddingNd();
1715 mImpl->setWindowSize(windowSize);
1725 return mImpl->getWindowSize();
1737 mImpl->setAlpha(alpha);
1747 return mImpl->getAlpha();
1759 mImpl->setBeta(beta);
1769 return mImpl->getBeta();
1791 return mImpl->getK();
1857 mImpl->setMode(mode);
1867 return mImpl->getMode();
1877 mImpl->setShift(shift);
1887 return mImpl->getShift();
1897 mImpl->setScale(scale);
1907 return mImpl->getScale();
1917 mImpl->setPower(power);
1927 return mImpl->getPower();
1942 return mImpl->getChannelAxis();
1963 mImpl->setChannelAxis(channelAxis);
2016 mImpl->setAxes(axes);
2026 return mImpl->getAxes();
2062 mImpl->setAxis(axis);
2072 return mImpl->getAxis();
2099 mImpl->setNbOutputMaps(nbOutputMaps);
2109 return mImpl->getNbOutputMaps();
2129 mImpl->setNbGroups(nbGroups);
2139 return mImpl->getNbGroups();
2153 mImpl->setKernelWeights(weights);
2163 return mImpl->getKernelWeights();
2178 mImpl->setBiasWeights(weights);
2188 return mImpl->getBiasWeights();
2206 mImpl->setPrePadding(padding);
2216 return mImpl->getPrePadding();
2234 mImpl->setPostPadding(padding);
2244 return mImpl->getPostPadding();
2258 mImpl->setPaddingMode(paddingMode);
2270 return mImpl->getPaddingMode();
2285 mImpl->setKernelSizeNd(kernelSize);
2295 return mImpl->getKernelSizeNd();
2312 mImpl->setStrideNd(stride);
2322 return mImpl->getStrideNd();
2340 mImpl->setPaddingNd(padding);
2352 return mImpl->getPaddingNd();
2378 mImpl->setDilationNd(dilation);
2388 return mImpl->getDilationNd();
2438 static constexpr int32_t kVALUE = 14;
2475 return mImpl->setOperation(op);
2487 return mImpl->getOperation();
2609 mImpl->setGatherAxis(axis);
2621 return mImpl->getGatherAxis();
2644 mImpl->setNbElementWiseDims(elementWiseDims);
2654 return mImpl->getNbElementWiseDims();
2664 mImpl->setMode(mode);
2674 return mImpl->getMode();
2701 return mImpl->getPlugin();
2728 return mImpl->getPlugin();
2810 mImpl->setOperation(op);
2820 return mImpl->getOperation();
2883 mImpl->setOperation(op);
2893 return mImpl->getOperation();
2903 mImpl->setReduceAxes(reduceAxes);
2913 return mImpl->getReduceAxes();
2923 mImpl->setKeepDimensions(keepDimensions);
2933 return mImpl->getKeepDimensions();
2965 mImpl->setPrePaddingNd(padding);
2977 return mImpl->getPrePaddingNd();
2991 mImpl->setPostPaddingNd(padding);
3003 return mImpl->getPostPaddingNd();
3053 mImpl->setFirstTranspose(permutation);
3065 return mImpl->getFirstTranspose();
3090 mImpl->setReshapeDimensions(dimensions);
3103 return mImpl->getReshapeDimensions();
3150 mImpl->setSecondTranspose(permutation);
3162 return mImpl->getSecondTranspose();
3178 return mImpl->setZeroIsPlaceholder(zeroIsPlaceholder);
3191 return mImpl->getZeroIsPlaceholder();
3282 mImpl->setStart(start);
3297 return mImpl->getStart();
3311 return mImpl->setSize(size);
3326 return mImpl->getSize();
3340 mImpl->setStride(stride);
3355 return mImpl->getStride();
3365 mImpl->setMode(mode);
3375 return mImpl->getMode();
3470 mImpl->setOperation(op);
3480 return mImpl->getOperation();
3508 return mImpl->getK();
3518 mImpl->setReduceAxes(reduceAxes);
3528 return mImpl->getReduceAxes();
3630 mImpl->setOperation(index, op);
3642 return mImpl->getOperation(index);
3751 mImpl->setToType(toType);
3762 return mImpl->getToType();
3791 mImpl->setWeights(weights);
3801 return mImpl->getWeights();
3813 mImpl->setDimensions(dimensions);
3825 return mImpl->getDimensions();
3871 static constexpr int32_t kVALUE = 3;
3925 static constexpr int32_t kVALUE = 3;
3955 static constexpr int32_t kVALUE = 2;
3991 static constexpr int32_t kVALUE = 4;
4054 return mImpl->setOutputDimensions(dimensions);
4064 return mImpl->getOutputDimensions();
4092 void setScales(
float const* scales, int32_t nbScales)
noexcept
4094 mImpl->setScales(scales, nbScales);
4111 int32_t
getScales(int32_t size,
float* scales)
const noexcept
4113 return mImpl->getScales(size, scales);
4125 mImpl->setResizeMode(interpolationMode);
4135 return mImpl->getResizeMode();
4170 mImpl->setCoordinateTransformation(coordTransform);
4180 return mImpl->getCoordinateTransformation();
4195 mImpl->setSelectorForSinglePixel(selector);
4205 return mImpl->getSelectorForSinglePixel();
4219 mImpl->setNearestRounding(value);
4229 return mImpl->getNearestRounding();
4251 mImpl->setCubicCoeff(A);
4261 return mImpl->getCubicCoeff();
4274 mImpl->setExcludeOutside(excludeFlag);
4284 return mImpl->getExcludeOutside();
4354 return mBoundary->getLoop();
4359 apiv::VLoopBoundaryLayer* mBoundary;
4377 return mBoundary->getConditional();
4382 apiv::VConditionalBoundaryLayer* mBoundary;
4463 return mImpl->setCondition(condition);
4479 return mImpl->addOutput(trueSubgraphOutput, falseSubgraphOutput);
4491 return mImpl->addInput(input);
4506 mImpl->setName(name);
4516 return mImpl->getName();
4584 return mImpl->getLoopOutput();
4601 mImpl->setAxis(axis);
4609 return mImpl->getAxis();
4652 return mImpl->getTripLimit();
4673 mImpl->setAxis(axis);
4681 return mImpl->getAxis();
4695 mImpl->setReverse(reverse);
4705 return mImpl->getReverse();
4729 return mImpl->addRecurrence(initialValue);
4750 return mImpl->addTripLimit(tensor, limit);
4763 return mImpl->addIterator(tensor, axis, reverse);
4776 return mImpl->addLoopOutput(tensor, outputKind, axis);
4791 mImpl->setName(name);
4801 return mImpl->getName();
4851 mImpl->setMessage(message);
4861 return mImpl->getMessage();
4963 mImpl->setDimensions(dimensions);
4978 return mImpl->getDimensions();
4988 mImpl->setOperation(op);
4998 return mImpl->getOperation();
5017 mImpl->setAlpha(alpha);
5032 return mImpl->getAlpha();
5051 mImpl->setBeta(beta);
5066 return mImpl->getBeta();
5127 mImpl->setAlphaInt64(alpha);
5142 return mImpl->getAlphaInt64();
5161 mImpl->setBetaInt64(beta);
5176 return mImpl->getBetaInt64();
5184 return mImpl->isAlphaBetaInt64();
5201 mImpl->setToType(toType);
5213 return mImpl->getToType();
5307 return mImpl->getAxis();
5318 mImpl->setAxis(axis);
5334 mImpl->setToType(toType);
5346 return mImpl->getToType();
5437 return mImpl->getAxis();
5448 mImpl->setAxis(axis);
5464 mImpl->setToType(toType);
5476 return mImpl->getToType();
5534 return mImpl->setEquation(equation);
5544 return mImpl->getEquation();
5642 mImpl->setMode(mode);
5652 return mImpl->getMode();
5662 mImpl->setAxis(axis);
5670 return mImpl->getAxis();
5714 mImpl->setAxis(axis);
5722 return mImpl->getAxis();
5750 mImpl->setInterpolationMode(mode);
5762 return mImpl->getInterpolationMode();
5772 mImpl->setAlignCorners(alignCorners);
5784 return mImpl->getAlignCorners();
5796 return mImpl->setSampleMode(mode);
5808 return mImpl->getSampleMode();
5902 mImpl->setBoundingBoxFormat(fmt);
5914 return mImpl->getBoundingBoxFormat();
5928 mImpl->setTopKBoxLimit(limit);
5938 return mImpl->getTopKBoxLimit();
5991 mImpl->setBatchAxis(batchAxis);
6001 return mImpl->getBatchAxis();
6014 mImpl->setSequenceAxis(sequenceAxis);
6024 return mImpl->getSequenceAxis();
6062 return mImpl->setEpsilon(eps);
6072 return mImpl->getEpsilon();
6082 return mImpl->setAxes(axesMask);
6092 return mImpl->getAxes();
6113 return mImpl->setNbGroups(nbGroups);
6123 return mImpl->getNbGroups();
6148 return mImpl->setComputePrecision(type);
6158 return mImpl->getComputePrecision();
6226 return mImpl->addInput(name, type, dimensions);
6240 mImpl->markOutput(tensor);
6258 return mImpl->markDebug(tensor);
6274 return mImpl->unmarkDebug(tensor);
6284 return mImpl->isDebugTensor(tensor);
6304 return mImpl->addActivation(input, type);
6323 return mImpl->addLRN(input, window, alpha, beta, k);
6349 return mImpl->addScale(input, mode, shift, scale, power);
6362 return mImpl->addSoftMax(input);
6379 return mImpl->addConcatenation(inputs, nbInputs);
6406 return mImpl->addElementWise(input1, input2, op);
6428 return mImpl->addUnary(input, operation);
6442 return mImpl->addShuffle(input);
6459 return mImpl->addOneHot(indices, values, depth, axis);
6471 return mImpl->getNbLayers();
6485 return mImpl->getLayer(index);
6497 return mImpl->getNbInputs();
6513 return mImpl->getInput(index);
6527 return mImpl->getNbOutputs();
6543 return mImpl->getOutput(index);
6570 return mImpl->addReduce(input, operation, reduceAxes, keepDimensions);
6602 return mImpl->addTopK(input, op, k, reduceAxes);
6618 return mImpl->addGather(data, indices, axis);
6634 return mImpl->addGatherV2(data, indices, mode);
6653 return mImpl->addRaggedSoftMax(input, bounds);
6675 return mImpl->addMatrixMultiply(input0, op0, input1, op1);
6689 return mImpl->addNonZero(input);
6713 return mImpl->addConstant(dimensions, weights);
6727 return mImpl->addIdentity(input);
6742 return mImpl->addCast(input, toType);
6757 mImpl->removeTensor(tensor);
6769 mImpl->unmarkOutput(tensor);
6788 return mImpl->addPluginV2(inputs, nbInputs, plugin);
6805 int32_t nbShapeInputs,
IPluginV3& plugin)
noexcept
6807 return mImpl->addPluginV3(inputs, nbInputs, shapeInputs, nbShapeInputs, plugin);
6826 return mImpl->addSlice(input, start, size, stride);
6850 mImpl->setName(name);
6864 return mImpl->getName();
6880 return mImpl->addShape(input);
6894 return mImpl->hasImplicitBatchDimension();
6904 return mImpl->getFlags();
6916 return mImpl->getFlag(networkDefinitionCreationFlag);
6933 return mImpl->markOutputForShapes(tensor);
6945 return mImpl->unmarkOutputForShapes(tensor);
6963 return mImpl->addParametricReLU(input, slope);
6986 return mImpl->addConvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7005 return mImpl->addPoolingNd(input, type, windowSize);
7028 return mImpl->addDeconvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7065 return mImpl->addScaleNd(input, mode, shift, scale, power, channelAxis);
7081 return mImpl->addResize(input);
7095 return mImpl->addLoop();
7110 return mImpl->addIfConditional();
7149 return mImpl->addSelect(condition, thenInput, elseInput);
7166 return mImpl->addAssertion(condition, message);
7191 return mImpl->addFill(dimensions, op);
7217 return mImpl->addFillV2(dimensions, op, outputType);
7233 return mImpl->addPaddingNd(input, prePadding, postPadding);
7257 return mImpl->setWeightsName(weights, name);
7276 mImpl->setErrorRecorder(recorder);
7291 return mImpl->getErrorRecorder();
7312 return mImpl->addDequantize(input, scale);
7333 return mImpl->addDequantizeV2(input, scale, outputType);
7353 return mImpl->addScatter(data, indices, updates, mode);
7374 return mImpl->addQuantize(input, scale);
7395 return mImpl->addQuantizeV2(input, scale, outputType);
7410 return mImpl->addEinsum(inputs, nbInputs, equation);
7428 return mImpl->addGridSample(input, grid);
7446 return mImpl->addNMS(boxes, scores, maxOutputBoxesPerClass);
7463 return mImpl->addReverseSequence(input, sequenceLens);
7489 return mImpl->addNormalization(input, scale, bias, axesMask);
7500 return mImpl->getBuilder();
7568 virtual
bool getBatch(
void* bindings[],
char const* names[], int32_t nbBindings) noexcept = 0;
7584 virtual
void const* readCalibrationCache(std::
size_t& length) noexcept = 0;
7594 virtual
void writeCalibrationCache(
void const* ptr, std::
size_t length) noexcept = 0;
7754 virtual
double getRegressionCutoff() const noexcept = 0;
7768 virtual
void const* readHistogramCache(std::
size_t& length) noexcept = 0;
7778 virtual
void writeHistogramCache(
void const* ptr, std::
size_t length) noexcept = 0;
7817 return mImpl->getDataType();
7828 return mImpl->getStrides();
7838 return mImpl->getVectorizedDim();
7849 return mImpl->getComponentsPerElement();
7876 return mImpl->getImplementation();
7884 return mImpl->getTactic();
7910 return mImpl->getName();
7922 return mImpl->getDimensions(index, select);
7930 return mImpl->getNbInputs();
7938 return mImpl->getNbOutputs();
7965 return mImpl->getAlgorithmVariant();
7973 return mImpl->getTimingMSec();
7981 return mImpl->getWorkspaceSize();
7995 return mImpl->getAlgorithmIOInfoByIndex(index);
8030 int32_t nbChoices, int32_t* selection)
noexcept = 0;
8043 int32_t nbAlgorithms)
noexcept = 0;
8274 return mImpl->serialize();
8298 return mImpl->combine(inputCache, ignoreMismatch);
8308 return mImpl->reset();
8413 static constexpr int32_t kVALUE = 1;
8450 static constexpr int32_t kVALUE = 2;
8489 virtual void phaseStart(
char const* phaseName,
char const* parentPhase, int32_t nbSteps)
noexcept = 0;
8503 virtual bool stepComplete(
char const* phaseName, int32_t step)
noexcept = 0;
8562 virtual
void setAvgTimingIterations(int32_t avgTiming) noexcept
8564 mImpl->setAvgTimingIterations(avgTiming);
8576 return mImpl->getAvgTimingIterations();
8589 mImpl->setEngineCapability(capability);
8601 return mImpl->getEngineCapability();
8611 mImpl->setInt8Calibrator(calibrator);
8619 return mImpl->getInt8Calibrator();
8636 mImpl->setFlags(builderFlags);
8648 return mImpl->getFlags();
8660 mImpl->clearFlag(builderFlag);
8672 mImpl->setFlag(builderFlag);
8684 return mImpl->getFlag(builderFlag);
8701 mImpl->setDeviceType(layer, deviceType);
8711 return mImpl->getDeviceType(layer);
8723 return mImpl->isDeviceTypeSet(layer);
8733 mImpl->resetDeviceType(layer);
8743 return mImpl->canRunOnDLA(layer);
8759 mImpl->setDLACore(dlaCore);
8769 return mImpl->getDLACore();
8780 mImpl->setDefaultDeviceType(deviceType);
8790 return mImpl->getDefaultDeviceType();
8812 return mImpl->setProfileStream(stream);
8824 return mImpl->getProfileStream();
8841 return mImpl->addOptimizationProfile(profile);
8854 return mImpl->getNbOptimizationProfiles();
8866 mImpl->setProfilingVerbosity(verbosity);
8879 return mImpl->getProfilingVerbosity();
8888 mImpl->setAlgorithmSelector(selector);
8896 return mImpl->getAlgorithmSelector();
8912 return mImpl->setCalibrationProfile(profile);
8922 return mImpl->getCalibrationProfile();
8939 mImpl->setQuantizationFlags(flags);
8951 return mImpl->getQuantizationFlags();
8963 mImpl->clearQuantizationFlag(flag);
8975 mImpl->setQuantizationFlag(flag);
8987 return mImpl->getQuantizationFlag(flag);
9009 return mImpl->setTacticSources(tacticSources);
9024 return mImpl->getTacticSources();
9043 return mImpl->createTimingCache(blob, size);
9066 return mImpl->setTimingCache(cache, ignoreMismatch);
9076 return mImpl->getTimingCache();
9108 mImpl->setMemoryPoolLimit(pool, poolSize);
9127 return mImpl->getMemoryPoolLimit(pool);
9145 mImpl->setPreviewFeature(feature, enable);
9159 return mImpl->getPreviewFeature(feature);
9192 mImpl->setBuilderOptimizationLevel(level);
9204 return mImpl->getBuilderOptimizationLevel();
9221 mImpl->setHardwareCompatibilityLevel(hardwareCompatibilityLevel);
9234 return mImpl->getHardwareCompatibilityLevel();
9247 mImpl->setPluginsToSerialize(paths, nbPaths);
9260 return mImpl->getPluginToSerialize(index);
9270 return mImpl->getNbPluginsToSerialize();
9299 mImpl->setMaxAuxStreams(nbStreams);
9309 return mImpl->getMaxAuxStreams();
9325 return mImpl->setProgressMonitor(monitor);
9335 return mImpl->getProgressMonitor();
9399 bool platformHasFastFp16() const noexcept
9401 return mImpl->platformHasFastFp16();
9409 return mImpl->platformHasFastInt8();
9421 return mImpl->getMaxDLABatchSize();
9429 return mImpl->getNbDLACores();
9446 mImpl->setGpuAllocator(allocator);
9456 return mImpl->createBuilderConfig();
9478 return mImpl->createNetworkV2(flags);
9493 return mImpl->createOptimizationProfile();
9512 mImpl->setErrorRecorder(recorder);
9527 return mImpl->getErrorRecorder();
9543 return mImpl->platformHasTf32();
9562 return mImpl->buildSerializedNetwork(network, config);
9584 return mImpl->isNetworkSupported(network, config);
9594 return mImpl->getLogger();
9610 return mImpl->setMaxThreads(maxThreads);
9624 return mImpl->getMaxThreads();
9634 return mImpl->getPluginRegistry();
9647extern "C" TENSORRTAPI void* createInferBuilder_INTERNAL(
void* logger, int32_t version)
noexcept;
#define TENSORRTAPI
Definition: NvInferRuntimeBase.h:59
#define NV_TENSORRT_VERSION
Definition: NvInferRuntimeBase.h:87
#define TRT_DEPRECATED
Definition: NvInferRuntimeBase.h:45
#define TRT_DEPRECATED_ENUM
Definition: NvInferRuntimeBase.h:46
Definition: NvInferRuntimeBase.h:195
static constexpr int32_t MAX_DIMS
The maximum rank (number of dimensions) supported for a tensor.
Definition: NvInferRuntimeBase.h:198
An Activation layer in a network definition.
Definition: NvInfer.h:1337
void setBeta(float beta) noexcept
Set the beta parameter (must be finite).
Definition: NvInfer.h:1385
void setActivationType(ActivationType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1346
ActivationType getActivationType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1356
float getAlpha() const noexcept
Get the alpha parameter.
Definition: NvInfer.h:1394
virtual ~IActivationLayer() noexcept=default
float getBeta() const noexcept
Get the beta parameter.
Definition: NvInfer.h:1403
void setAlpha(float alpha) noexcept
Set the alpha parameter (must be finite).
Definition: NvInfer.h:1371
Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorith...
Definition: NvInfer.h:7901
int32_t getNbOutputs() const noexcept
Return number of outputs of the algorithm.
Definition: NvInfer.h:7936
int32_t getNbInputs() const noexcept
Return number of inputs of the algorithm.
Definition: NvInfer.h:7928
char const * getName() const noexcept
Return name of the algorithm node.
Definition: NvInfer.h:7908
virtual ~IAlgorithmContext() noexcept=default
Dims getDimensions(int32_t index, OptProfileSelector select) const noexcept
Get the minimum / optimum / maximum dimensions for input or output tensor.
Definition: NvInfer.h:7920
Describes a variation of execution of a layer. An algorithm is represented by IAlgorithmVariant and t...
Definition: NvInfer.h:7958
std::size_t getWorkspaceSize() const noexcept
The size of the GPU temporary memory in bytes which the algorithm uses at execution time.
Definition: NvInfer.h:7979
float getTimingMSec() const noexcept
The time in milliseconds to execute the algorithm.
Definition: NvInfer.h:7971
IAlgorithmIOInfo const * getAlgorithmIOInfoByIndex(int32_t index) const noexcept
Returns the format of an Algorithm input or output. Algorithm inputs are incrementally numbered first...
Definition: NvInfer.h:7993
virtual ~IAlgorithm() noexcept=default
IAlgorithmVariant const & getAlgorithmVariant() const noexcept
Returns the algorithm variant.
Definition: NvInfer.h:7963
Carries information about input or output of the algorithm. IAlgorithmIOInfo for all the input and ou...
Definition: NvInfer.h:7808
virtual ~IAlgorithmIOInfo() noexcept=default
int64_t getVectorizedDim() const noexcept
Return the index of the vectorized dimension or -1 for non-vectorized formats.
Definition: NvInfer.h:7836
Dims getStrides() const noexcept
Return strides of the input/output tensor of algorithm. For vectorized formats, strides are given in ...
Definition: NvInfer.h:7826
DataType getDataType() const noexcept
Return DataType of the input/output of algorithm.
Definition: NvInfer.h:7815
int64_t getComponentsPerElement() const noexcept
Return the number of components per element. This is always 1 for non-vectorized formats.
Definition: NvInfer.h:7847
provides a unique 128-bit identifier, which along with the input and output information denotes the v...
Definition: NvInfer.h:7869
virtual ~IAlgorithmVariant() noexcept=default
int64_t getTactic() const noexcept
Return tactic of the algorithm.
Definition: NvInfer.h:7882
int64_t getImplementation() const noexcept
Return implementation of the algorithm.
Definition: NvInfer.h:7874
An assertion layer in a network.
Definition: NvInfer.h:4839
void setMessage(char const *message) noexcept
Set the message to print if the assertion fails.
Definition: NvInfer.h:4849
char const * getMessage() const noexcept
Return the assertion message.
Definition: NvInfer.h:4859
virtual ~IAssertionLayer() noexcept=default
Holds properties for configuring a builder to produce an engine.
Definition: NvInfer.h:8550
IOptimizationProfile const * getCalibrationProfile() noexcept
Get the current calibration profile.
Definition: NvInfer.h:8920
void setMemoryPoolLimit(MemoryPoolType pool, std::size_t poolSize) noexcept
Set the memory size for the memory pool.
Definition: NvInfer.h:9106
void setQuantizationFlag(QuantizationFlag flag) noexcept
Set a single quantization flag.
Definition: NvInfer.h:8973
nvinfer1::ITimingCache * createTimingCache(void const *blob, std::size_t size) const noexcept
Create timing cache.
Definition: NvInfer.h:9041
void setPreviewFeature(PreviewFeature feature, bool enable) noexcept
Enable or disable a specific preview feature.
Definition: NvInfer.h:9143
void setInt8Calibrator(IInt8Calibrator *calibrator) noexcept
Set Int8 Calibration interface.
Definition: NvInfer.h:8609
bool getPreviewFeature(PreviewFeature feature) const noexcept
Get status of preview feature.
Definition: NvInfer.h:9157
void clearQuantizationFlag(QuantizationFlag flag) noexcept
clear a quantization flag.
Definition: NvInfer.h:8961
int32_t getBuilderOptimizationLevel() noexcept
Get builder optimization level.
Definition: NvInfer.h:9202
bool setTacticSources(TacticSources tacticSources) noexcept
Set tactic sources.
Definition: NvInfer.h:9007
void setPluginsToSerialize(char const *const *paths, int32_t nbPaths) noexcept
Set the plugin libraries to be serialized with version-compatible engines.
Definition: NvInfer.h:9245
bool getQuantizationFlag(QuantizationFlag flag) const noexcept
Returns true if the quantization flag is set.
Definition: NvInfer.h:8985
std::size_t getMemoryPoolLimit(MemoryPoolType pool) const noexcept
Get the memory size limit of the memory pool.
Definition: NvInfer.h:9125
int32_t getDLACore() const noexcept
Get the DLA core that the engine executes on.
Definition: NvInfer.h:8767
int32_t getNbPluginsToSerialize() const noexcept
Get the number of plugin library paths to be serialized with version-compatible engines.
Definition: NvInfer.h:9268
void setDeviceType(ILayer const *layer, DeviceType deviceType) noexcept
Set the device that this layer must execute on.
Definition: NvInfer.h:8699
void setEngineCapability(EngineCapability capability) noexcept
Configure the builder to target specified EngineCapability flow.
Definition: NvInfer.h:8587
int32_t getMaxAuxStreams() const noexcept
Get the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9307
bool getFlag(BuilderFlag builderFlag) const noexcept
Returns true if the build mode flag is set.
Definition: NvInfer.h:8682
void setQuantizationFlags(QuantizationFlags flags) noexcept
Set the quantization flags.
Definition: NvInfer.h:8937
bool setCalibrationProfile(IOptimizationProfile const *profile) noexcept
Add a calibration profile.
Definition: NvInfer.h:8910
void setProgressMonitor(IProgressMonitor *monitor) noexcept
Sets the progress monitor for building a network.
Definition: NvInfer.h:9323
void setProfilingVerbosity(ProfilingVerbosity verbosity) noexcept
Set verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:8864
IAlgorithmSelector * getAlgorithmSelector() const noexcept
Get Algorithm Selector.
Definition: NvInfer.h:8894
int32_t getNbOptimizationProfiles() const noexcept
Get number of optimization profiles.
Definition: NvInfer.h:8852
QuantizationFlags getQuantizationFlags() const noexcept
Get the quantization flags.
Definition: NvInfer.h:8949
nvinfer1::ITimingCache const * getTimingCache() const noexcept
Get the pointer to the timing cache from current IBuilderConfig.
Definition: NvInfer.h:9074
void reset() noexcept
Resets the builder configuration to defaults.
Definition: NvInfer.h:8798
bool setTimingCache(ITimingCache const &cache, bool ignoreMismatch) noexcept
Attach a timing cache to IBuilderConfig.
Definition: NvInfer.h:9064
char const * getPluginToSerialize(int32_t index) const noexcept
Get the plugin library path to be serialized with version-compatible engines.
Definition: NvInfer.h:9258
EngineCapability getEngineCapability() const noexcept
Query EngineCapability flow configured for the builder.
Definition: NvInfer.h:8599
void setAlgorithmSelector(IAlgorithmSelector *selector) noexcept
Set Algorithm Selector.
Definition: NvInfer.h:8886
DeviceType getDefaultDeviceType() const noexcept
Get the default DeviceType which was set by setDefaultDeviceType.
Definition: NvInfer.h:8788
BuilderFlags getFlags() const noexcept
Get the build mode flags for this builder config. Defaults to 0.
Definition: NvInfer.h:8646
void setFlags(BuilderFlags builderFlags) noexcept
Set the build mode flags to turn on builder options for this network.
Definition: NvInfer.h:8634
TacticSources getTacticSources() const noexcept
Get tactic sources.
Definition: NvInfer.h:9022
void resetDeviceType(ILayer const *layer) noexcept
reset the DeviceType for this layer
Definition: NvInfer.h:8731
void setDLACore(int32_t dlaCore) noexcept
Sets the DLA core used by the network. Defaults to -1.
Definition: NvInfer.h:8757
HardwareCompatibilityLevel getHardwareCompatibilityLevel() const noexcept
Get the hardware compatibility level.
Definition: NvInfer.h:9232
void clearFlag(BuilderFlag builderFlag) noexcept
clear a single build mode flag.
Definition: NvInfer.h:8658
int32_t addOptimizationProfile(IOptimizationProfile const *profile) noexcept
Add an optimization profile.
Definition: NvInfer.h:8839
IProgressMonitor * getProgressMonitor() const noexcept
Definition: NvInfer.h:9333
apiv::VBuilderConfig * mImpl
Definition: NvInfer.h:9339
int32_t getAvgTimingIterations() const noexcept
Query the number of averaging iterations.
Definition: NvInfer.h:8574
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:8778
void setFlag(BuilderFlag builderFlag) noexcept
Set a single build mode flag.
Definition: NvInfer.h:8670
virtual ~IBuilderConfig() noexcept=default
DeviceType getDeviceType(ILayer const *layer) const noexcept
Get the device that this layer executes on.
Definition: NvInfer.h:8709
bool canRunOnDLA(ILayer const *layer) const noexcept
Checks if a layer can run on DLA.
Definition: NvInfer.h:8741
cudaStream_t getProfileStream() const noexcept
Get the cuda stream that is used to profile this network.
Definition: NvInfer.h:8822
void setHardwareCompatibilityLevel(HardwareCompatibilityLevel hardwareCompatibilityLevel) noexcept
Set the hardware compatibility level.
Definition: NvInfer.h:9219
IInt8Calibrator * getInt8Calibrator() const noexcept
Get Int8 Calibration interface.
Definition: NvInfer.h:8617
void setMaxAuxStreams(int32_t nbStreams) noexcept
Set the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:9297
ProfilingVerbosity getProfilingVerbosity() const noexcept
Get verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:8877
bool isDeviceTypeSet(ILayer const *layer) const noexcept
whether the DeviceType has been explicitly set for this layer
Definition: NvInfer.h:8721
void setBuilderOptimizationLevel(int32_t level) noexcept
Set builder optimization level.
Definition: NvInfer.h:9190
void setProfileStream(const cudaStream_t stream) noexcept
Set the cuda stream that is used to profile this network.
Definition: NvInfer.h:8810
Builds an engine from a network definition.
Definition: NvInfer.h:9392
int32_t getMaxDLABatchSize() const noexcept
Get the maximum batch size DLA can support. For any tensor the total volume of index dimensions combi...
Definition: NvInfer.h:9419
int32_t getNbDLACores() const noexcept
Return the number of DLA engines available to this builder.
Definition: NvInfer.h:9427
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:9525
apiv::VBuilder * mImpl
Definition: NvInfer.h:9638
ILogger * getLogger() const noexcept
get the logger with which the builder was created
Definition: NvInfer.h:9592
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:9582
bool platformHasTf32() const noexcept
Determine whether the platform has TF32 support.
Definition: NvInfer.h:9541
int32_t getMaxThreads() const noexcept
get the maximum number of threads that can be used by the builder.
Definition: NvInfer.h:9622
IPluginRegistry & getPluginRegistry() noexcept
get the local plugin registry that can be used by the builder.
Definition: NvInfer.h:9632
nvinfer1::IOptimizationProfile * createOptimizationProfile() noexcept
Create a new optimization profile.
Definition: NvInfer.h:9491
void setGpuAllocator(IGpuAllocator *allocator) noexcept
Set the GPU allocator.
Definition: NvInfer.h:9444
nvinfer1::INetworkDefinition * createNetworkV2(NetworkDefinitionCreationFlags flags) noexcept
Create a network definition object.
Definition: NvInfer.h:9476
nvinfer1::IBuilderConfig * createBuilderConfig() noexcept
Create a builder configuration object.
Definition: NvInfer.h:9454
void reset() noexcept
Resets the builder state to default values.
Definition: NvInfer.h:9533
bool setMaxThreads(int32_t maxThreads) noexcept
Set the maximum number of threads.
Definition: NvInfer.h:9608
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:9510
bool platformHasFastInt8() const noexcept
Determine whether the platform has fast native int8.
Definition: NvInfer.h:9407
nvinfer1::IHostMemory * buildSerializedNetwork(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds and serializes a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:9560
virtual ~IBuilder() noexcept=default
A cast layer in a network.
Definition: NvInfer.h:3740
virtual ~ICastLayer() noexcept=default
apiv::VCastLayer * mImpl
Definition: NvInfer.h:3766
DataType getToType() const noexcept
Return cast layer output type.
Definition: NvInfer.h:3760
void setToType(DataType toType) noexcept
Set cast layer output type.
Definition: NvInfer.h:3749
A concatenation layer in a network definition.
Definition: NvInfer.h:2047
void setAxis(int32_t axis) noexcept
Set the axis along which concatenation occurs.
Definition: NvInfer.h:2060
int32_t getAxis() const noexcept
Get the axis along which concatenation occurs.
Definition: NvInfer.h:2070
virtual ~IConcatenationLayer() noexcept=default
This layer represents a condition input to an IIfConditional.
Definition: NvInfer.h:4391
virtual ~IConditionLayer() noexcept=default
Layer that represents a constant value.
Definition: NvInfer.h:3779
void setWeights(Weights weights) noexcept
Set the weights for the layer.
Definition: NvInfer.h:3789
Weights getWeights() const noexcept
Get the weights for the layer.
Definition: NvInfer.h:3799
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions for the layer.
Definition: NvInfer.h:3811
apiv::VConstantLayer * mImpl
Definition: NvInfer.h:3829
virtual ~IConstantLayer() noexcept=default
Dims getDimensions() const noexcept
Get the dimensions for the layer.
Definition: NvInfer.h:3823
A convolution layer in a network definition.
Definition: NvInfer.h:1017
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1142
Weights getBiasWeights() const noexcept
Get the bias weights for the convolution.
Definition: NvInfer.h:1115
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1183
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1287
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the convolution.
Definition: NvInfer.h:1273
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the convolution.
Definition: NvInfer.h:1243
Weights getKernelWeights() const noexcept
Get the kernel weights of the convolution.
Definition: NvInfer.h:1090
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the convolution.
Definition: NvInfer.h:1233
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1297
int64_t getNbOutputMaps() const noexcept
Get the number of output maps for the convolution.
Definition: NvInfer.h:1036
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the convolution.
Definition: NvInfer.h:1080
Dims getPostPadding() const noexcept
Get the post-padding.
Definition: NvInfer.h:1169
int64_t getNbGroups() const noexcept
Get the number of groups of the convolution.
Definition: NvInfer.h:1066
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1195
virtual ~IConvolutionLayer() noexcept=default
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a convolution.
Definition: NvInfer.h:1056
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output maps for the convolution.
Definition: NvInfer.h:1026
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the convolution.
Definition: NvInfer.h:1105
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1218
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the convolution.
Definition: NvInfer.h:1261
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the convolution.
Definition: NvInfer.h:1132
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the convolution.
Definition: NvInfer.h:1159
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1208
A deconvolution layer in a network definition.
Definition: NvInfer.h:2088
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the deconvolution.
Definition: NvInfer.h:2176
int64_t getNbGroups() const noexcept
Get the number of groups for a deconvolution.
Definition: NvInfer.h:2137
Weights getKernelWeights() const noexcept
Get the kernel weights for the deconvolution.
Definition: NvInfer.h:2161
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the deconvolution.
Definition: NvInfer.h:2204
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2320
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2386
Weights getBiasWeights() const noexcept
Get the bias weights for the deconvolution.
Definition: NvInfer.h:2186
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the deconvolution.
Definition: NvInfer.h:2151
int64_t getNbOutputMaps() const noexcept
Get the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2107
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2310
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:2242
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2293
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the deconvolution.
Definition: NvInfer.h:2232
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2283
virtual ~IDeconvolutionLayer() noexcept=default
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2338
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2097
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2350
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2376
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:2256
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a deconvolution.
Definition: NvInfer.h:2127
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:2214
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:2268
A Dequantize layer in a network definition.
Definition: NvInfer.h:5425
void setToType(DataType toType) noexcept
Set the Dequantize layer output type.
Definition: NvInfer.h:5462
virtual ~IDequantizeLayer() noexcept=default
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5435
DataType getToType() const noexcept
Return the Dequantize layer output type.
Definition: NvInfer.h:5474
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5446
An Einsum layer in a network.
Definition: NvInfer.h:5521
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:5532
virtual ~IEinsumLayer() noexcept=default
char const * getEquation() const noexcept
Return the equation.
Definition: NvInfer.h:5542
A elementwise layer in a network definition.
Definition: NvInfer.h:2462
virtual ~IElementWiseLayer() noexcept=default
apiv::VElementWiseLayer * mImpl
Definition: NvInfer.h:2491
ElementWiseOperation getOperation() const noexcept
Get the binary operation for the layer.
Definition: NvInfer.h:2485
void setOperation(ElementWiseOperation op) noexcept
Set the binary operation for the layer.
Definition: NvInfer.h:2473
Generate a tensor according to a specified mode.
Definition: NvInfer.h:4950
bool isAlphaBetaInt64() const noexcept
Return true if alpha/beta have type int64, false if they have type double.
Definition: NvInfer.h:5182
FillOperation getOperation() const noexcept
Get the fill operation for the layer.
Definition: NvInfer.h:4996
void setOperation(FillOperation op) noexcept
Set the fill operation for the layer.
Definition: NvInfer.h:4986
DataType getToType() const noexcept
Get the fill layer output type.
Definition: NvInfer.h:5211
void setAlphaInt64(int64_t alpha) noexcept
Set the alpha parameter with int64 datatype.
Definition: NvInfer.h:5125
void setBetaInt64(int64_t beta) noexcept
Set the beta parameter with int64 datatype.
Definition: NvInfer.h:5159
void setBeta(double beta) noexcept
Set the beta parameter.
Definition: NvInfer.h:5049
int64_t getAlphaInt64() const noexcept
Get the value of alpha parameter with int64 datatype.
Definition: NvInfer.h:5140
int64_t getBetaInt64() const noexcept
Get the value of beta parameter with int64 datatype.
Definition: NvInfer.h:5174
double getAlpha() const noexcept
Get the value of alpha parameter.
Definition: NvInfer.h:5030
void setDimensions(Dims const &dimensions) noexcept
Set the output tensor's dimensions.
Definition: NvInfer.h:4961
void setAlpha(double alpha) noexcept
Set the alpha parameter.
Definition: NvInfer.h:5015
void setToType(DataType toType) noexcept
Set the fill layer output type.
Definition: NvInfer.h:5199
Dims getDimensions() const noexcept
Get the output tensor's dimensions.
Definition: NvInfer.h:4976
double getBeta() const noexcept
Get the value of beta parameter.
Definition: NvInfer.h:5064
virtual ~IFillLayer() noexcept=default
A Gather layer in a network definition. Supports several kinds of gathering.
Definition: NvInfer.h:2596
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:2607
void setNbElementWiseDims(int32_t elementWiseDims) noexcept
Set the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2642
apiv::VGatherLayer * mImpl
Definition: NvInfer.h:2678
int32_t getNbElementWiseDims() const noexcept
Get the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2652
void setMode(GatherMode mode) noexcept
Set the gather mode.
Definition: NvInfer.h:2662
int32_t getGatherAxis() const noexcept
Get the axis to gather on.
Definition: NvInfer.h:2619
GatherMode getMode() const noexcept
Get the gather mode.
Definition: NvInfer.h:2672
virtual ~IGatherLayer() noexcept=default
A GridSample layer in a network definition.
Definition: NvInfer.h:5741
void setInterpolationMode(InterpolationMode mode) noexcept
Set the grid sample interpolation mode.
Definition: NvInfer.h:5748
bool setSampleMode(SampleMode mode) noexcept
Set the sample mode.
Definition: NvInfer.h:5794
void setAlignCorners(bool alignCorners) noexcept
Set the align corners mode.
Definition: NvInfer.h:5770
apiv::VGridSampleLayer * mImpl
Definition: NvInfer.h:5812
SampleMode getSampleMode() const noexcept
Get the sample mode.
Definition: NvInfer.h:5806
InterpolationMode getInterpolationMode() const noexcept
Get the grid sample interpolation mode.
Definition: NvInfer.h:5760
bool getAlignCorners() const noexcept
Get the align corners mode.
Definition: NvInfer.h:5782
virtual ~IGridSampleLayer() noexcept=default
Class to handle library allocated memory that is accessible to the user.
Definition: NvInferRuntime.h:139
A layer that represents the identity function.
Definition: NvInfer.h:3727
apiv::VIdentityLayer * mImpl
Definition: NvInfer.h:3729
virtual ~IIdentityLayer() noexcept=default
This is a base class for Conditional boundary layers.
Definition: NvInfer.h:4370
IIfConditional * getConditional() const noexcept
Get a pointer to the IIfConditional associated with this boundary layer.
Definition: NvInfer.h:4375
virtual ~IIfConditionalBoundaryLayer() noexcept=default
Helper for constructing conditionally-executed subgraphs.
Definition: NvInfer.h:4450
IIfConditionalInputLayer * addInput(ITensor &input) noexcept
Add an If-conditional input.
Definition: NvInfer.h:4489
char const * getName() const noexcept
Return the name of the conditional.
Definition: NvInfer.h:4514
virtual ~IIfConditional() noexcept=default
IConditionLayer * setCondition(ITensor &condition) noexcept
Set the condition tensor for this If-Conditional construct.
Definition: NvInfer.h:4461
IIfConditionalOutputLayer * addOutput(ITensor &trueSubgraphOutput, ITensor &falseSubgraphOutput) noexcept
Add an If-conditional output.
Definition: NvInfer.h:4477
void setName(char const *name) noexcept
Set the name of the conditional.
Definition: NvInfer.h:4504
This layer represents an output of an IIfConditional.
Definition: NvInfer.h:4406
virtual ~IIfConditionalOutputLayer() noexcept=default
Application-implemented interface for calibration.
Definition: NvInfer.h:7543
virtual TRT_DEPRECATED int32_t getBatchSize() const noexcept=0
Get the batch size used for calibration batches.
A layer to do iterations.
Definition: NvInfer.h:4666
virtual ~IIteratorLayer() noexcept=default
void setReverse(bool reverse) noexcept
Set iteration order to be reverse.
Definition: NvInfer.h:4693
bool getReverse() const noexcept
Check if the iteration order is reverse.
Definition: NvInfer.h:4703
int32_t getAxis() const noexcept
Get axis being iterated over.
Definition: NvInfer.h:4679
void setAxis(int32_t axis) noexcept
Set axis to iterate over.
Definition: NvInfer.h:4671
A LRN layer in a network definition.
Definition: NvInfer.h:1702
int64_t getWindowSize() const noexcept
Get the LRN window size.
Definition: NvInfer.h:1723
float getAlpha() const noexcept
Get the LRN alpha value.
Definition: NvInfer.h:1745
void setWindowSize(int64_t windowSize) noexcept
Set the LRN window size.
Definition: NvInfer.h:1713
void setK(float k) noexcept
Set the LRN K value.
Definition: NvInfer.h:1779
void setAlpha(float alpha) noexcept
Set the LRN alpha value.
Definition: NvInfer.h:1735
void setBeta(float beta) noexcept
Set the LRN beta value.
Definition: NvInfer.h:1757
virtual ~ILRNLayer() noexcept=default
float getBeta() const noexcept
Get the LRN beta value.
Definition: NvInfer.h:1767
float getK() const noexcept
Get the LRN K value.
Definition: NvInfer.h:1789
Base class for all layer classes in a network definition.
Definition: NvInfer.h:544
bool precisionIsSet() const noexcept
whether the computational precision has been set for this layer
Definition: NvInfer.h:687
void setMetadata(char const *metadata) noexcept
Set the metadata for this layer.
Definition: NvInfer.h:803
void setPrecision(DataType dataType) noexcept
Set the preferred or required computational precision of this layer in a weakly-typed network.
Definition: NvInfer.h:663
void setName(char const *name) noexcept
Set the name of a layer.
Definition: NvInfer.h:565
void resetPrecision() noexcept
reset the computational precision for this layer
Definition: NvInfer.h:697
int32_t getNbInputs() const noexcept
Get the number of inputs of a layer.
Definition: NvInfer.h:583
char const * getMetadata() const noexcept
Get the metadata of the layer.
Definition: NvInfer.h:816
DataType getOutputType(int32_t index) const noexcept
get the output type of this layer
Definition: NvInfer.h:759
DataType getPrecision() const noexcept
get the computational precision of this layer
Definition: NvInfer.h:675
char const * getName() const noexcept
Return the name of a layer.
Definition: NvInfer.h:575
int32_t getNbOutputs() const noexcept
Get the number of outputs of a layer.
Definition: NvInfer.h:604
bool outputTypeIsSet(int32_t index) const noexcept
whether the output type has been set for this layer
Definition: NvInfer.h:773
ITensor * getOutput(int32_t index) const noexcept
Get the layer output corresponding to the given index.
Definition: NvInfer.h:614
void setInput(int32_t index, ITensor &tensor) noexcept
Replace an input of this layer with a specific tensor.
Definition: NvInfer.h:631
void resetOutputType(int32_t index) noexcept
reset the output type for this layer
Definition: NvInfer.h:785
ITensor * getInput(int32_t index) const noexcept
Get the layer input corresponding to the given index.
Definition: NvInfer.h:596
void setOutputType(int32_t index, DataType dataType) noexcept
Set the output type of this layer in a weakly-typed network.
Definition: NvInfer.h:744
LayerType getType() const noexcept
Return the type of a layer.
Definition: NvInfer.h:551
virtual ~ILayer() noexcept=default
Application-implemented logging interface for the builder, refitter and runtime.
Definition: NvInferRuntimeBase.h:676
This is a base class for Loop boundary layers.
Definition: NvInfer.h:4347
virtual ~ILoopBoundaryLayer() noexcept=default
ILoop * getLoop() const noexcept
Get a pointer to ILoop associated with this boundary layer.
Definition: NvInfer.h:4352
Helper for creating a recurrent subgraph.
Definition: NvInfer.h:4719
void setName(char const *name) noexcept
Set the name of the loop.
Definition: NvInfer.h:4789
ITripLimitLayer * addTripLimit(ITensor &tensor, TripLimit limit) noexcept
Add a trip-count limiter, based on the given tensor.
Definition: NvInfer.h:4748
IIteratorLayer * addIterator(ITensor &tensor, int32_t axis=0, bool reverse=false) noexcept
Return layer that subscripts tensor by loop iteration.
Definition: NvInfer.h:4761
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:4774
virtual ~ILoop() noexcept=default
char const * getName() const noexcept
Return the name of the loop.
Definition: NvInfer.h:4799
IRecurrenceLayer * addRecurrence(ITensor &initialValue) noexcept
Create a recurrence layer for this loop with initialValue as its first input.
Definition: NvInfer.h:4727
An ILoopOutputLayer is the sole way to get output from a loop.
Definition: NvInfer.h:4577
virtual ~ILoopOutputLayer() noexcept=default
int32_t getAxis() const noexcept
Get axis being concatenated over.
Definition: NvInfer.h:4607
LoopOutput getLoopOutput() const noexcept
Get which kind a loop output has.
Definition: NvInfer.h:4582
void setAxis(int32_t axis) noexcept
Set where to insert the contenation axis. Ignored if getLoopOutput() is kLAST_VALUE.
Definition: NvInfer.h:4599
Layer that represents a Matrix Multiplication.
Definition: NvInfer.h:3618
apiv::VMatrixMultiplyLayer * mImpl
Definition: NvInfer.h:3646
virtual ~IMatrixMultiplyLayer() noexcept=default
MatrixOperation getOperation(int32_t index) const noexcept
Get the operation for an input tensor.
Definition: NvInfer.h:3640
void setOperation(int32_t index, MatrixOperation op) noexcept
Set the operation for an input tensor.
Definition: NvInfer.h:3628
A non-maximum suppression layer in a network definition.
Definition: NvInfer.h:5889
virtual ~INMSLayer() noexcept=default
void setTopKBoxLimit(int32_t limit) noexcept
Set the TopK box limit parameter for the layer.
Definition: NvInfer.h:5926
void setBoundingBoxFormat(BoundingBoxFormat fmt) noexcept
Set the bounding box format parameter for the layer.
Definition: NvInfer.h:5900
BoundingBoxFormat getBoundingBoxFormat() const noexcept
Get the bounding box format parameter for the layer.
Definition: NvInfer.h:5912
apiv::VNMSLayer * mImpl
Definition: NvInfer.h:5962
int32_t getTopKBoxLimit() const noexcept
Get the TopK box limit parameter for the layer.
Definition: NvInfer.h:5936
A network definition for input to the builder.
Definition: NvInfer.h:6184
IPluginV2Layer * addPluginV2(ITensor *const *inputs, int32_t nbInputs, IPluginV2 &plugin) noexcept
Add a plugin layer to the network using the IPluginV2 interface.
Definition: NvInfer.h:6786
IConcatenationLayer * addConcatenation(ITensor *const *inputs, int32_t nbInputs) noexcept
Add a concatenation layer to the network.
Definition: NvInfer.h:6377
IShuffleLayer * addShuffle(ITensor &input) noexcept
Add a shuffle layer to the network.
Definition: NvInfer.h:6440
INormalizationLayer * addNormalization(ITensor &input, ITensor &scale, ITensor &bias, uint32_t axesMask) noexcept
Add a normalization layer to the network.
Definition: NvInfer.h:7487
void setName(char const *name) noexcept
Sets the name of the network.
Definition: NvInfer.h:6848
bool markDebug(ITensor &tensor) noexcept
Mark a tensor as a debug tensor.
Definition: NvInfer.h:6256
ILRNLayer * addLRN(ITensor &input, int64_t window, float alpha, float beta, float k) noexcept
Add a LRN layer to the network.
Definition: NvInfer.h:6321
ITopKLayer * addTopK(ITensor &input, TopKOperation op, int32_t k, uint32_t reduceAxes) noexcept
Add a TopK layer to the network.
Definition: NvInfer.h:6600
IAssertionLayer * addAssertion(ITensor &condition, char const *message) noexcept
Add an assertion layer to the network.
Definition: NvInfer.h:7164
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:6983
ICastLayer * addCast(ITensor &input, DataType toType) noexcept
Add a cast layer.
Definition: NvInfer.h:6740
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:7062
char const * getName() const noexcept
Returns the name associated with the network.
Definition: NvInfer.h:6862
IParametricReLULayer * addParametricReLU(ITensor &input, ITensor &slope) noexcept
Add a parametric ReLU layer to the network.
Definition: NvInfer.h:6961
ITensor * getOutput(int32_t index) const noexcept
Get the output tensor specified by the given index.
Definition: NvInfer.h:6541
ITensor * getInput(int32_t index) const noexcept
Get the input tensor specified by the given index.
Definition: NvInfer.h:6511
IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7331
bool unmarkOutputForShapes(ITensor &tensor) noexcept
Undo markOutputForShapes.
Definition: NvInfer.h:6943
IFillLayer * addFill(Dims const &dimensions, FillOperation op, DataType outputType) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7215
ILoop * addLoop() noexcept
Add a loop to the network.
Definition: NvInfer.h:7093
IActivationLayer * addActivation(ITensor &input, ActivationType type) noexcept
Add an activation layer to the network.
Definition: NvInfer.h:6302
TRT_DEPRECATED IFillLayer * addFill(Dims const &dimensions, FillOperation op) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7189
ISliceLayer * addSlice(ITensor &input, Dims const &start, Dims const &size, Dims const &stride) noexcept
Add a slice layer to the network.
Definition: NvInfer.h:6824
virtual ~INetworkDefinition() noexcept=default
TRT_DEPRECATED IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7372
virtual IBuilder & getBuilder() const noexcept
Return the builder from which this INetworkDefinition was created.
Definition: NvInfer.h:7498
INMSLayer * addNMS(ITensor &boxes, ITensor &scores, ITensor &maxOutputBoxesPerClass) noexcept
Add a non-maximum suppression layer to the network.
Definition: NvInfer.h:7444
ILayer * getLayer(int32_t index) const noexcept
Get the layer specified by the given index.
Definition: NvInfer.h:6483
bool getFlag(NetworkDefinitionCreationFlag networkDefinitionCreationFlag) const noexcept
Returns true if the network definition creation flag is set.
Definition: NvInfer.h:6914
IIfConditional * addIfConditional() noexcept
Add an if-then-else to the network.
Definition: NvInfer.h:7108
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:7289
IReverseSequenceLayer * addReverseSequence(ITensor &input, ITensor &sequenceLens) noexcept
Add a ReverseSequence layer to the network.
Definition: NvInfer.h:7461
int32_t getNbInputs() const noexcept
Get the number of inputs in the network.
Definition: NvInfer.h:6495
NetworkDefinitionCreationFlags getFlags() const noexcept
Get the network definition creation flags for this network definition object. Defaults to 0.
Definition: NvInfer.h:6902
IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7393
IReduceLayer * addReduce(ITensor &input, ReduceOperation operation, uint32_t reduceAxes, bool keepDimensions) noexcept
Add a reduce layer to the network.
Definition: NvInfer.h:6567
IUnaryLayer * addUnary(ITensor &input, UnaryOperation operation) noexcept
Add a unary layer to the network.
Definition: NvInfer.h:6426
IGridSampleLayer * addGridSample(ITensor &input, ITensor &grid) noexcept
Add a GridSample layer to the network.
Definition: NvInfer.h:7426
void removeTensor(ITensor &tensor) noexcept
remove a tensor from the network definition.
Definition: NvInfer.h:6755
ISelectLayer * addSelect(ITensor &condition, ITensor &thenInput, ITensor &elseInput) noexcept
Add a select layer to the network.
Definition: NvInfer.h:7147
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:7351
int32_t getNbLayers() const noexcept
Get the number of layers in the network.
Definition: NvInfer.h:6469
TRT_DEPRECATED bool hasImplicitBatchDimension() const noexcept
Query whether the network was created with an implicit batch dimension.
Definition: NvInfer.h:6892
apiv::VNetworkDefinition * mImpl
Definition: NvInfer.h:7504
bool markOutputForShapes(ITensor &tensor) noexcept
Enable tensor's value to be computed by IExecutionContext::getShapeBinding.
Definition: NvInfer.h:6931
IOneHotLayer * addOneHot(ITensor &indices, ITensor &values, ITensor &depth, int32_t axis) noexcept
Add a OneHot layer to the network.
Definition: NvInfer.h:6457
IScaleLayer * addScale(ITensor &input, ScaleMode mode, Weights shift, Weights scale, Weights power) noexcept
Add a Scale layer to the network.
Definition: NvInfer.h:6347
IPluginV3Layer * addPluginV3(ITensor *const *inputs, int32_t nbInputs, ITensor *const *shapeInputs, int32_t nbShapeInputs, IPluginV3 &plugin) noexcept
Add a plugin layer implementing the IPluginV3 interface to the network.
Definition: NvInfer.h:6804
void unmarkOutput(ITensor &tensor) noexcept
unmark a tensor as a network output.
Definition: NvInfer.h:6767
IIdentityLayer * addIdentity(ITensor &input) noexcept
Add an identity layer.
Definition: NvInfer.h:6725
IGatherLayer * addGatherV2(ITensor &data, ITensor &indices, GatherMode mode) noexcept
Add gather with specified mode, axis=0 and nbElementWiseDims=0.
Definition: NvInfer.h:6632
IElementWiseLayer * addElementWise(ITensor &input1, ITensor &input2, ElementWiseOperation op) noexcept
Add an elementwise layer to the network.
Definition: NvInfer.h:6404
IConstantLayer * addConstant(Dims const &dimensions, Weights weights) noexcept
Add a constant layer to the network.
Definition: NvInfer.h:6711
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:7274
IPoolingLayer * addPoolingNd(ITensor &input, PoolingType type, Dims const &windowSize) noexcept
Add a multi-dimension pooling layer to the network.
Definition: NvInfer.h:7003
IRaggedSoftMaxLayer * addRaggedSoftMax(ITensor &input, ITensor &bounds) noexcept
Add a RaggedSoftMax layer to the network.
Definition: NvInfer.h:6651
IShapeLayer * addShape(ITensor &input) noexcept
Add a shape layer to the network.
Definition: NvInfer.h:6878
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:6616
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:7025
IResizeLayer * addResize(ITensor &input) noexcept
Add a resize layer to the network.
Definition: NvInfer.h:7079
IMatrixMultiplyLayer * addMatrixMultiply(ITensor &input0, MatrixOperation op0, ITensor &input1, MatrixOperation op1) noexcept
Add a MatrixMultiply layer to the network.
Definition: NvInfer.h:6672
ISoftMaxLayer * addSoftMax(ITensor &input) noexcept
Add a SoftMax layer to the network.
Definition: NvInfer.h:6360
bool isDebugTensor(nvinfer1::ITensor const &tensor) const noexcept
Check if a tensor is marked as debug tensor.
Definition: NvInfer.h:6282
bool unmarkDebug(ITensor &tensor) noexcept
Unmark a tensor as a debug tensor.
Definition: NvInfer.h:6272
IEinsumLayer * addEinsum(ITensor *const *inputs, int32_t nbInputs, char const *equation) noexcept
Add an Einsum layer to the network.
Definition: NvInfer.h:7408
void markOutput(ITensor &tensor) noexcept
Mark a tensor as a network output.
Definition: NvInfer.h:6238
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:7231
INonZeroLayer * addNonZero(ITensor &input) noexcept
Add a nonzero layer to the network.
Definition: NvInfer.h:6687
TRT_DEPRECATED IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7310
int32_t getNbOutputs() const noexcept
Get the number of outputs in the network.
Definition: NvInfer.h:6525
bool setWeightsName(Weights weights, char const *name) noexcept
Associate a name with all current uses of the given weights.
Definition: NvInfer.h:7255
Forward declaration of IEngineInspector for use by other interfaces.
Definition: NvInferRuntime.h:48
Definition: NvInfer.h:3672
virtual ~INonZeroLayer() noexcept=default
A normalization layer in a network definition.
Definition: NvInfer.h:6051
float getEpsilon() const noexcept
Get the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6070
uint32_t getAxes() const noexcept
Get the axes value used for the normalization calculation.
Definition: NvInfer.h:6090
virtual ~INormalizationLayer() noexcept=default
void setEpsilon(float eps) noexcept
Set the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6060
DataType getComputePrecision() const noexcept
Get the compute precision of this layer.
Definition: NvInfer.h:6156
apiv::VNormalizationLayer * mImpl
Definition: NvInfer.h:6162
int64_t getNbGroups() const noexcept
Get the number of groups used to split the channels for the normalization calculation.
Definition: NvInfer.h:6121
void setAxes(uint32_t axesMask) noexcept
Set the reduction axes for the normalization calculation.
Definition: NvInfer.h:6080
void setComputePrecision(DataType type) noexcept
Set the compute precision of this layer.
Definition: NvInfer.h:6146
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups used to split the channels in the normalization calculation.
Definition: NvInfer.h:6111
A OneHot layer in a network definition.
Definition: NvInfer.h:5705
apiv::VOneHotLayer * mImpl
Definition: NvInfer.h:5726
void setAxis(int32_t axis) noexcept
Set the axis parameter.
Definition: NvInfer.h:5712
int32_t getAxis() const noexcept
Get the value of the axis parameter.
Definition: NvInfer.h:5720
Optimization profile for dynamic input dimensions and shape tensors.
Definition: NvInferRuntime.h:2075
Layer that represents a padding operation.
Definition: NvInfer.h:2952
Dims getPostPaddingNd() const noexcept
Get the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3001
void setPrePaddingNd(Dims const &padding) noexcept
Set the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2963
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:2989
Dims getPrePaddingNd() const noexcept
Get the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2975
apiv::VPaddingLayer * mImpl
Definition: NvInfer.h:3007
Layer that represents a parametric ReLU operation.
Definition: NvInfer.h:3843
apiv::VParametricReLULayer * mImpl
Definition: NvInfer.h:3845
virtual ~IParametricReLULayer() noexcept=default
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferRuntimeCommon.h:54
Plugin class for user-implemented layers.
Definition: NvInferRuntimePlugin.h:126
Layer type for pluginV2.
Definition: NvInfer.h:2692
virtual ~IPluginV2Layer() noexcept=default
apiv::VPluginV2Layer * mImpl
Definition: NvInfer.h:2705
IPluginV2 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:2699
Layer type for V3 plugins.
Definition: NvInfer.h:2719
virtual ~IPluginV3Layer() noexcept=default
IPluginV3 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:2726
apiv::VPluginV3Layer * mImpl
Definition: NvInfer.h:2732
A Pooling layer in a network definition.
Definition: NvInfer.h:1451
PoolingType getPoolingType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1470
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1603
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:1579
bool getAverageCountExcludesPadding() const noexcept
Get whether average pooling uses as a denominator the overlap area between the window and the unpadde...
Definition: NvInfer.h:1523
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1551
void setPoolingType(PoolingType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1460
void setWindowSizeNd(Dims const &windowSize) noexcept
Set the multi-dimension window size for pooling.
Definition: NvInfer.h:1616
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1592
Dims getWindowSizeNd() const noexcept
Get the multi-dimension window size for pooling.
Definition: NvInfer.h:1626
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:1512
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding for pooling.
Definition: NvInfer.h:1670
float getBlendFactor() const noexcept
Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1498
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride for pooling.
Definition: NvInfer.h:1641
Dims getStrideNd() const noexcept
Get the multi-dimension stride for pooling.
Definition: NvInfer.h:1651
virtual ~IPoolingLayer() noexcept=default
Dims getPaddingNd() const noexcept
Get the multi-dimension padding for pooling.
Definition: NvInfer.h:1682
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding for pooling.
Definition: NvInfer.h:1569
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding for pooling.
Definition: NvInfer.h:1541
void setBlendFactor(float blendFactor) noexcept
Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1485
A Quantize layer in a network definition.
Definition: NvInfer.h:5295
void setToType(DataType toType) noexcept
Set the Quantize layer output type.
Definition: NvInfer.h:5332
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5316
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5305
virtual ~IQuantizeLayer() noexcept=default
DataType getToType() const noexcept
Return the Quantize layer output type.
Definition: NvInfer.h:5344
A RaggedSoftmax layer in a network definition.
Definition: NvInfer.h:3693
apiv::VRaggedSoftMaxLayer * mImpl
Definition: NvInfer.h:3695
virtual ~IRaggedSoftMaxLayer() noexcept=default
A recurrence layer in a network definition.
Definition: NvInfer.h:4530
virtual ~IRecurrenceLayer() noexcept=default
Layer that represents a reduction across a non-bool tensor.
Definition: NvInfer.h:2874
void setKeepDimensions(bool keepDimensions) noexcept
Set the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2921
void setOperation(ReduceOperation op) noexcept
Set the reduce operation for the layer.
Definition: NvInfer.h:2881
ReduceOperation getOperation() const noexcept
Get the reduce operation for the layer.
Definition: NvInfer.h:2891
virtual ~IReduceLayer() noexcept=default
uint32_t getReduceAxes() const noexcept
Get the axes over which to reduce for the layer.
Definition: NvInfer.h:2911
void setReduceAxes(uint32_t reduceAxes) noexcept
Set the axes over which to reduce.
Definition: NvInfer.h:2901
apiv::VReduceLayer * mImpl
Definition: NvInfer.h:2937
bool getKeepDimensions() const noexcept
Get the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2931
A resize layer in a network definition.
Definition: NvInfer.h:4032
void setSelectorForSinglePixel(ResizeSelector selector) noexcept
Set coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4193
void setNearestRounding(ResizeRoundMode value) noexcept
Set rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4217
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:4111
void setOutputDimensions(Dims const &dimensions) noexcept
Set the output dimensions.
Definition: NvInfer.h:4052
void setCubicCoeff(float A) noexcept
Set the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4249
void setScales(float const *scales, int32_t nbScales) noexcept
Set the resize scales.
Definition: NvInfer.h:4092
float getCubicCoeff() const noexcept
Get the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4259
ResizeSelector getSelectorForSinglePixel() const noexcept
Get the coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4203
InterpolationMode getResizeMode() const noexcept
Get resize mode for an input tensor.
Definition: NvInfer.h:4133
void setCoordinateTransformation(ResizeCoordinateTransformation coordTransform) noexcept
Set coordinate transformation function.
Definition: NvInfer.h:4168
void setExcludeOutside(bool excludeFlag) noexcept
Set the state for excluding outside pixels.
Definition: NvInfer.h:4272
void setResizeMode(InterpolationMode interpolationMode) noexcept
Set resize mode for an input tensor.
Definition: NvInfer.h:4123
Dims getOutputDimensions() const noexcept
Get the output dimensions.
Definition: NvInfer.h:4062
ResizeRoundMode getNearestRounding() const noexcept
Get rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4227
bool getExcludeOutside() const noexcept
Get the state for excluding outside pixels.
Definition: NvInfer.h:4282
ResizeCoordinateTransformation getCoordinateTransformation() const noexcept
Get coordinate transformation function.
Definition: NvInfer.h:4178
A ReverseSequence layer in a network definition.
Definition: NvInfer.h:5979
void setSequenceAxis(int32_t sequenceAxis) noexcept
Set the sequence axis. Default is 0.
Definition: NvInfer.h:6012
int32_t getBatchAxis() const noexcept
Return the batch axis. Return 1 if no batch axis was set.
Definition: NvInfer.h:5999
apiv::VReverseSequenceLayer * mImpl
Definition: NvInfer.h:6028
int32_t getSequenceAxis() const noexcept
Return the sequence axis. Return 0 if no sequence axis was set.
Definition: NvInfer.h:6022
void setBatchAxis(int32_t batchAxis) noexcept
Set the batch axis. Default is 1.
Definition: NvInfer.h:5989
virtual ~IReverseSequenceLayer() noexcept=default
A Scale layer in a network definition.
Definition: NvInfer.h:1848
Weights getScale() const noexcept
Get the scale value.
Definition: NvInfer.h:1905
Weights getPower() const noexcept
Get the power value.
Definition: NvInfer.h:1925
void setScale(Weights scale) noexcept
Set the scale value.
Definition: NvInfer.h:1895
void setPower(Weights power) noexcept
Set the power value.
Definition: NvInfer.h:1915
ScaleMode getMode() const noexcept
Get the scale mode.
Definition: NvInfer.h:1865
void setShift(Weights shift) noexcept
Set the shift value.
Definition: NvInfer.h:1875
void setChannelAxis(int32_t channelAxis) noexcept
Set the channel axis.
Definition: NvInfer.h:1961
Weights getShift() const noexcept
Get the shift value.
Definition: NvInfer.h:1885
virtual ~IScaleLayer() noexcept=default
void setMode(ScaleMode mode) noexcept
Set the scale mode.
Definition: NvInfer.h:1855
int32_t getChannelAxis() const noexcept
Get the channel axis.
Definition: NvInfer.h:1940
A scatter layer in a network definition. Supports several kinds of scattering.
Definition: NvInfer.h:5633
void setMode(ScatterMode mode) noexcept
Set the scatter mode.
Definition: NvInfer.h:5640
apiv::VScatterLayer * mImpl
Definition: NvInfer.h:5674
void setAxis(int32_t axis) noexcept
Set the axis used by ScatterMode::kELEMENTS.
Definition: NvInfer.h:5660
int32_t getAxis() const noexcept
Get the axis.
Definition: NvInfer.h:5668
ScatterMode getMode() const noexcept
Get the scatter mode.
Definition: NvInfer.h:5650
virtual ~IScatterLayer() noexcept=default
A select layer in a network definition.
Definition: NvInfer.h:4817
virtual ~ISelectLayer() noexcept=default
Layer type for getting shape of a tensor.
Definition: NvInfer.h:3421
virtual ~IShapeLayer() noexcept=default
apiv::VShapeLayer * mImpl
Definition: NvInfer.h:3423
Layer type for shuffling data.
Definition: NvInfer.h:3040
apiv::VShuffleLayer * mImpl
Definition: NvInfer.h:3195
void setFirstTranspose(Permutation permutation) noexcept
Set the permutation applied by the first transpose operation.
Definition: NvInfer.h:3051
void setSecondTranspose(Permutation permutation) noexcept
Set the permutation applied by the second transpose operation.
Definition: NvInfer.h:3148
Dims getReshapeDimensions() const noexcept
Get the reshaped dimensions.
Definition: NvInfer.h:3101
void setReshapeDimensions(Dims const &dimensions) noexcept
Set the reshaped dimensions.
Definition: NvInfer.h:3088
Permutation getFirstTranspose() const noexcept
Get the permutation applied by the first transpose operation.
Definition: NvInfer.h:3063
virtual ~IShuffleLayer() noexcept=default
Permutation getSecondTranspose() const noexcept
Get the permutation applied by the second transpose operation.
Definition: NvInfer.h:3160
bool getZeroIsPlaceholder() const noexcept
Get meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3189
void setZeroIsPlaceholder(bool zeroIsPlaceholder) noexcept
Set meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3176
Slices an input tensor into an output tensor based on the offset and strides.
Definition: NvInfer.h:3269
void setStride(Dims const &stride) noexcept
Set the stride for computing the output slice data.
Definition: NvInfer.h:3338
apiv::VSliceLayer * mImpl
Definition: NvInfer.h:3404
virtual ~ISliceLayer() noexcept=default
void setSize(Dims const &size) noexcept
Set the dimensions of the output slice.
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:3280
Dims getStart() const noexcept
Get the start offset for the slice layer.
Definition: NvInfer.h:3295
void setMode(SampleMode mode) noexcept
Set the slice mode.
Definition: NvInfer.h:3363
Dims getSize() const noexcept
Get dimensions of the output slice.
Definition: NvInfer.h:3324
SampleMode getMode() const noexcept
Get the slice mode.
Definition: NvInfer.h:3373
Dims getStride() const noexcept
Get the stride for the output slice.
Definition: NvInfer.h:3353
A Softmax layer in a network definition.
Definition: NvInfer.h:1992
void setAxes(uint32_t axes) noexcept
Set the axis along which softmax is computed. Currently, only one axis can be set.
Definition: NvInfer.h:2014
uint32_t getAxes() const noexcept
Get the axis along which softmax occurs.
Definition: NvInfer.h:2024
virtual ~ISoftMaxLayer() noexcept=default
A tensor in a network definition.
Definition: NvInfer.h:181
bool setDynamicRange(float min, float max) noexcept
Set dynamic range for the tensor.
Definition: NvInfer.h:284
void setAllowedFormats(TensorFormats formats) noexcept
Set allowed formats for this tensor. By default all formats are allowed. Shape tensors (for which isS...
Definition: NvInfer.h:420
TensorLocation getLocation() const noexcept
Get the storage location of a tensor.
Definition: NvInfer.h:343
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions of a tensor.
Definition: NvInfer.h:228
void resetDynamicRange() noexcept
Undo effect of setDynamicRange.
Definition: NvInfer.h:380
void setName(char const *name) noexcept
Set the tensor name.
Definition: NvInfer.h:197
bool isExecutionTensor() const noexcept
Whether the tensor is an execution tensor.
Definition: NvInfer.h:485
void setType(DataType type) noexcept
Set the data type of a tensor.
Definition: NvInfer.h:257
bool dynamicRangeIsSet() const noexcept
Query whether dynamic range is set.
Definition: NvInfer.h:372
char const * getName() const noexcept
Get the tensor name.
Definition: NvInfer.h:209
bool isShapeTensor() const noexcept
Whether the tensor is a shape tensor.
Definition: NvInfer.h:464
float getDynamicRangeMax() const noexcept
Get maximum of dynamic range.
Definition: NvInfer.h:400
bool isNetworkInput() const noexcept
Whether the tensor is a network input.
Definition: NvInfer.h:292
TRT_DEPRECATED void setBroadcastAcrossBatch(bool broadcastAcrossBatch) noexcept
Set whether to enable broadcast of tensor across the implicit batch dimension.
Definition: NvInfer.h:317
TRT_DEPRECATED bool getBroadcastAcrossBatch() const noexcept
Check if tensor is broadcast across the implicit batch dimension.
Definition: NvInfer.h:331
bool isNetworkOutput() const noexcept
Whether the tensor is a network output.
Definition: NvInfer.h:300
DataType getType() const noexcept
Get the data type of a tensor.
Definition: NvInfer.h:269
apiv::VTensor * mImpl
Definition: NvInfer.h:532
float getDynamicRangeMin() const noexcept
Get minimum of dynamic range.
Definition: NvInfer.h:390
virtual ~ITensor() noexcept=default
void setDimensionName(int32_t index, char const *name) noexcept
Name a dimension of an input tensor.
Definition: NvInfer.h:511
char const * getDimensionName(int32_t index) const noexcept
Get the name of an input dimension.
Definition: NvInfer.h:526
TRT_DEPRECATED void setLocation(TensorLocation location) noexcept
Set the storage location of a tensor.
Definition: NvInfer.h:362
Dims getDimensions() const noexcept
Get the dimensions of a tensor.
Definition: NvInfer.h:242
TensorFormats getAllowedFormats() const noexcept
Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor,...
Definition: NvInfer.h:433
Class to handle tactic timing info collected from builder.
Definition: NvInfer.h:8259
bool combine(ITimingCache const &inputCache, bool ignoreMismatch) noexcept
Combine input timing cache into local instance.
Definition: NvInfer.h:8296
virtual ~ITimingCache() noexcept=default
apiv::VTimingCache * mImpl
Definition: NvInfer.h:8312
bool reset() noexcept
Empty the timing cache.
Definition: NvInfer.h:8306
Layer that represents a TopK reduction.
Definition: NvInfer.h:3461
void setK(int32_t k) noexcept
Set the static k value for the layer.
Definition: NvInfer.h:3492
void setReduceAxes(uint32_t reduceAxes) noexcept
Set which axes to reduce for the layer.
Definition: NvInfer.h:3516
TopKOperation getOperation() const noexcept
Get the operation for the layer.
Definition: NvInfer.h:3478
apiv::VTopKLayer * mImpl
Definition: NvInfer.h:3548
void setOperation(TopKOperation op) noexcept
Set the operation for the layer.
Definition: NvInfer.h:3468
int32_t getK() const noexcept
Get the k value for the layer.
Definition: NvInfer.h:3506
uint32_t getReduceAxes() const noexcept
Get the axes to reduce for the layer.
Definition: NvInfer.h:3526
virtual ~ITopKLayer() noexcept=default
A layer that represents a trip-count limiter.
Definition: NvInfer.h:4645
TripLimit getTripLimit() const noexcept
Get a trip limiter type.
Definition: NvInfer.h:4650
virtual ~ITripLimitLayer() noexcept=default
Layer that represents an unary operation.
Definition: NvInfer.h:2799
void setOperation(UnaryOperation op) noexcept
Set the unary operation for the layer.
Definition: NvInfer.h:2808
apiv::VUnaryLayer * mImpl
Definition: NvInfer.h:2824
UnaryOperation getOperation() const noexcept
Get the unary operation for the layer.
Definition: NvInfer.h:2818
virtual ~IUnaryLayer() noexcept=default
An Interface class for version control.
Definition: NvInferRuntimeBase.h:393
Version information associated with a TRT interface.
Definition: NvInferRuntimeBase.h:358
An array of weights used as a layer parameter.
Definition: NvInferRuntime.h:121
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferSafeRuntime.h:828
Definition: NvInfer.h:8006
virtual int32_t selectAlgorithms(IAlgorithmContext const &context, IAlgorithm const *const *choices, int32_t nbChoices, int32_t *selection) noexcept=0
Select Algorithms for a layer from the given list of algorithm choices.
virtual void reportAlgorithms(IAlgorithmContext const *const *algoContexts, IAlgorithm const *const *algoChoices, int32_t nbAlgorithms) noexcept=0
Called by TensorRT to report choices it made.
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:8011
virtual ~IAlgorithmSelector() noexcept=default
Definition: NvInferRuntimeBase.h:850
Definition: NvInferRuntimeBase.h:462
Definition: NvInfer.h:7647
~IInt8EntropyCalibrator2() noexcept override=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7660
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7652
Definition: NvInfer.h:7609
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7622
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7614
~IInt8EntropyCalibrator() noexcept override=default
Definition: NvInfer.h:7722
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7735
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7727
virtual double getQuantile() const noexcept=0
The quantile (between 0 and 1) that will be used to select the region maximum when the quantile metho...
Definition: NvInfer.h:7685
~IInt8MinMaxCalibrator() noexcept override=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:7698
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:7690
Definition: NvInferRuntime.h:687
Definition: NvInfer.h:8457
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:9661
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:2292
ResizeSelector
The coordinate selector when resize to single pixel output.
Definition: NvInfer.h:3937
@ kFORMULA
Use formula to map the original index.
@ kUPPER
Select the upper left pixel.
EngineCapability
List of supported engine capability flows.
Definition: NvInferRuntime.h:73
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:8323
ScaleMode
Controls how shift, scale and power are applied in a Scale layer.
Definition: NvInfer.h:1805
@ kUNIFORM
Identical coefficients across all elements of the tensor.
@ kCHANNEL
Per-channel coefficients.
uint32_t QuantizationFlags
Represents one or more QuantizationFlag values using binary OR operations.
Definition: NvInfer.h:8067
HardwareCompatibilityLevel
Describes requirements of compatibility with GPU architectures other than that of the GPU on which th...
Definition: NvInfer.h:8428
BoundingBoxFormat
Representation of bounding box data used for the Boxes input tensor in INMSLayer.
Definition: NvInfer.h:5824
@ 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:8243
constexpr int32_t EnumMax< LayerType >() noexcept
Definition: NvInfer.h:114
constexpr int32_t EnumMax< CalibrationAlgoType >() noexcept
Definition: NvInfer.h:7526
UnaryOperation
Enumerates the unary operations that may be performed by a Unary layer.
Definition: NvInfer.h:2753
@ kISINF
Return true if input value equals +/- infinity for floating-point data type.
@ kCOSH
Hyperbolic cosine.
@ kACOSH
Inverse hyperbolic cosine.
@ kERF
Gauss error function.
@ kROUND
Round to nearest even for floating-point data type.
@ kATANH
Inverse hyperbolic tangent.
@ kASINH
Inverse hyperbolic sine.
@ kSIGN
Sign, If input > 0, output 1; if input < 0, output -1; if input == 0, output 0.
constexpr int32_t EnumMax< ReduceOperation >() noexcept
Definition: NvInfer.h:2861
constexpr int32_t EnumMax< TripLimit >() noexcept
Definition: NvInfer.h:4334
ActivationType
Enumerates the types of activation to perform in an activation layer.
Definition: NvInfer.h:133
@ kSELU
Selu activation: x>0 ? beta * x : beta * (alpha*exp(x) - alpha)
@ kSCALED_TANH
Scaled tanh activation: alpha*tanh(beta*x)
@ kRELU
Rectified linear activation.
@ kELU
Elu activation: x>=0 ? x : alpha * (exp(x) - 1).
@ kLEAKY_RELU
LeakyRelu activation: x>=0 ? x : alpha * x.
@ kSOFTSIGN
Softsign activation: x / (1+|x|)
@ kHARD_SIGMOID
Hard sigmoid activation: max(0, min(1, alpha*x+beta))
@ kTHRESHOLDED_RELU
Thresholded ReLU activation: x>alpha ? x : 0.
@ kSIGMOID
Sigmoid activation.
@ kCLIP
Clip activation: max(alpha, min(beta, x))
@ kGELU_TANH
GELU tanh activation: 0.5 * x * (1 + tanh(sqrt(2/pi) * (0.044715F * pow(x, 3) + x)))
@ kGELU_ERF
GELU erf activation: 0.5 * x * (1 + erf(sqrt(0.5) * x))
@ kSOFTPLUS
Parametric softplus activation: alpha*log(exp(beta*x)+1)
FillOperation
Enumerates the tensor fill operations that may performed by a fill layer.
Definition: NvInfer.h:4878
@ 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:3967
@ 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:983
@ kSAME_LOWER
Use SAME padding, with prePadding >= postPadding.
@ kEXPLICIT_ROUND_DOWN
Use explicit padding, rounding output size down.
@ kEXPLICIT_ROUND_UP
Use explicit padding, rounding output size up.
@ kSAME_UPPER
Use SAME padding, with prePadding <= postPadding.
TripLimit
Definition: NvInfer.h:4322
@ 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:9349
PreviewFeature
Define preview features.
Definition: NvInfer.h:8395
constexpr int32_t EnumMax< GatherMode >() noexcept
Definition: NvInfer.h:2513
DataType
The type of weights and tensors.
Definition: NvInferRuntimeBase.h:129
uint32_t BuilderFlags
Represents one or more BuilderFlag values using binary OR operations, e.g., 1U << BuilderFlag::kFP16 ...
Definition: NvInfer.h:8101
DeviceType
The device that this layer/network will execute on.
Definition: NvInferRuntime.h:1252
constexpr int32_t EnumMax< ScaleMode >() noexcept
Definition: NvInfer.h:1817
CalibrationAlgoType
Version of calibration algorithm to use.
Definition: NvInfer.h:7513
@ kENTROPY_CALIBRATION_2
Entropy calibration.
@ kLEGACY_CALIBRATION
Legacy calibration.
@ kENTROPY_CALIBRATION
Legacy entropy calibration.
@ kMINMAX_CALIBRATION
Minmax calibration.
LayerType
The type values of layer classes.
Definition: NvInfer.h:58
@ kGRID_SAMPLE
Grid sample layer.
@ kRAGGED_SOFTMAX
Ragged softmax layer.
@ kDECONVOLUTION
Deconvolution layer.
@ kASSERTION
Assertion layer.
@ kMATRIX_MULTIPLY
Matrix multiply layer.
@ kCONDITION
Condition layer.
@ kCONDITIONAL_INPUT
Conditional Input layer.
@ kIDENTITY
Identity layer.
@ kNORMALIZATION
Normalization layer.
@ kQUANTIZE
Quantize layer.
@ kCONVOLUTION
Convolution layer.
@ kPARAMETRIC_RELU
Parametric ReLU layer.
@ kCONCATENATION
Concatenation layer.
@ kREVERSE_SEQUENCE
Reverse sequence layer.
@ kRECURRENCE
Loop Recurrence layer.
@ kDEQUANTIZE
Dequantize layer.
@ kPLUGIN_V3
PluginV3 layer.
@ kITERATOR
Loop Iterator layer.
@ kTRIP_LIMIT
Loop Trip limit layer.
@ kUNARY
UnaryOp operation Layer.
@ kACTIVATION
Activation layer.
@ kELEMENTWISE
Elementwise layer.
@ kPLUGIN_V2
PluginV2 layer.
@ kLOOP_OUTPUT
Loop output layer.
@ kCONDITIONAL_OUTPUT
Conditional Output layer.
@ kCONSTANT
Constant layer.
@ kNON_ZERO
NonZero layer.
constexpr int32_t EnumMax< QuantizationFlag >() noexcept
Definition: NvInfer.h:8090
SampleMode
Controls how ISliceLayer and IGridSample handle out-of-bounds coordinates.
Definition: NvInfer.h:3205
@ 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:2501
@ kDEFAULT
Similar to ONNX Gather.
@ kELEMENT
Similar to ONNX GatherElements.
@ kND
Similar to ONNX GatherND.
uint32_t TensorFormats
It is capable of representing one or more TensorFormat by binary OR operations, e....
Definition: NvInfer.h:125
ProfilingVerbosity
List of verbosity levels of layer information exposed in NVTX annotations and in IEngineInspector.
Definition: NvInferRuntime.h:2304
NetworkDefinitionCreationFlag
List of immutable network properties expressed at network creation time. NetworkDefinitionCreationFla...
Definition: NvInfer.h:9360
ElementWiseOperation
Enumerates the binary operations that may be performed by an ElementWise layer.
Definition: NvInfer.h:2411
@ 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.
QuantizationFlag
List of valid flags for quantizing the network to int8.
Definition: NvInfer.h:8077
@ kCALIBRATE_BEFORE_FUSION
constexpr int32_t EnumMax< SampleMode >() noexcept
Definition: NvInfer.h:3221
InterpolationMode
Enumerates various modes of interpolation.
Definition: NvInfer.h:3855
@ 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:8111
@ 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.
@ kFP16
Enable FP16 layer selection, with FP32 fallback.
@ kERROR_ON_TIMING_CACHE_MISS
@ kINT8
Enable Int8 layer selection, with FP32 fallback with FP16 fallback if kFP16 also specified.
@ kPREFER_PRECISION_CONSTRAINTS
@ kSTRIP_PLAN
Strip the refittable weights from the engine plan file.
@ kDISABLE_TIMING_CACHE
Disable reuse of timing information across identical layers.
@ kDISABLE_COMPILATION_CACHE
@ kREFIT
Enable building a refittable engine.
@ kOBEY_PRECISION_CONSTRAINTS
Require that layers execute in specified precisions. Build fails otherwise.
@ kREJECT_EMPTY_ALGORITHMS
Fail if IAlgorithmSelector::selectAlgorithms returns an empty set of algorithms.
constexpr int32_t EnumMax< TopKOperation >() noexcept
Definition: NvInfer.h:3444
constexpr int32_t EnumMax< MemoryPoolType >() noexcept
Definition: NvInfer.h:8381
TopKOperation
Enumerates the operations that may be performed by a TopK layer.
Definition: NvInfer.h:3433
ReduceOperation
Enumerates the reduce operations that may be performed by a Reduce layer.
Definition: NvInfer.h:2847
constexpr int32_t EnumMax< LoopOutput >() noexcept
Definition: NvInfer.h:4313
constexpr int32_t EnumMax< NetworkDefinitionCreationFlag >() noexcept
Definition: NvInfer.h:9379
ScatterMode
Control form of IScatterLayer.
Definition: NvInfer.h:5560
MatrixOperation
Enumerates the operations that may be performed on a tensor by IMatrixMultiplyLayer before multiplica...
Definition: NvInfer.h:3559
@ kTRANSPOSE
Like kNONE, but transpose the matrix dimensions.
ResizeCoordinateTransformation
The resize coordinate transformation function.
Definition: NvInfer.h:3883
constexpr int32_t EnumMax< UnaryOperation >() noexcept
Definition: NvInfer.h:2786
LoopOutput
Definition: NvInfer.h:4296
@ 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:5837
constexpr int32_t EnumMax< MatrixOperation >() noexcept
Definition: NvInfer.h:3587
PoolingType
The type of pooling to perform in a pooling layer.
Definition: NvInfer.h:1419
@ 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:8540
constexpr int32_t EnumMax< FillOperation >() noexcept
Definition: NvInfer.h:4909
TensorLocation
The location for tensor data storage, device or host.
Definition: NvInferRuntime.h:201
OptProfileSelector
When setting or querying optimization profile parameters (such as shape tensor inputs or dynamic dime...
Definition: NvInferRuntime.h:2035
constexpr int32_t EnumMax< ScatterMode >() noexcept
Definition: NvInfer.h:5571
Represents a permutation of dimensions.
Definition: NvInfer.h:3017
Declaration of EnumMaxImpl struct to store maximum number of elements in an enumeration type.
Definition: NvInferRuntimeBase.h:114