164 static constexpr int32_t kVALUE = 14;
204 mImpl->setName(name);
216 return mImpl->getName();
235 mImpl->setDimensions(dimensions);
249 return mImpl->getDimensions();
264 mImpl->setType(type);
276 return mImpl->getType();
293 return mImpl->setDynamicRange(min, max);
301 return mImpl->isNetworkInput();
309 return mImpl->isNetworkOutput();
326 mImpl->setBroadcastAcrossBatch(broadcastAcrossBatch);
340 return mImpl->getBroadcastAcrossBatch();
352 return mImpl->getLocation();
371 mImpl->setLocation(location);
383 return mImpl->dynamicRangeIsSet();
391 mImpl->resetDynamicRange();
401 return mImpl->getDynamicRangeMin();
411 return mImpl->getDynamicRangeMax();
433 mImpl->setAllowedFormats(formats);
446 return mImpl->getAllowedFormats();
477 return mImpl->isShapeTensor();
498 return mImpl->isExecutionTensor();
524 mImpl->setDimensionName(index, name);
539 return mImpl->getDimensionName(index);
564 return mLayer->getType();
578 mLayer->setName(name);
588 return mLayer->getName();
596 return mLayer->getNbInputs();
609 return mLayer->getInput(index);
617 return mLayer->getNbOutputs();
627 return mLayer->getOutput(index);
644 return mLayer->setInput(index, tensor);
675 mLayer->setPrecision(dataType);
687 return mLayer->getPrecision();
699 return mLayer->precisionIsSet();
709 mLayer->resetPrecision();
756 mLayer->setOutputType(index, dataType);
771 return mLayer->getOutputType(index);
785 return mLayer->outputTypeIsSet(index);
797 return mLayer->resetOutputType(index);
815 mLayer->setMetadata(metadata);
828 return mLayer->getMetadata();
833 apiv::VLayer* mLayer;
1010 static constexpr int32_t kVALUE = 4;
1038 mImpl->setNbOutputMaps(nbOutputMaps);
1048 return mImpl->getNbOutputMaps();
1068 mImpl->setNbGroups(nbGroups);
1078 return mImpl->getNbGroups();
1092 mImpl->setKernelWeights(weights);
1102 return mImpl->getKernelWeights();
1117 mImpl->setBiasWeights(weights);
1127 return mImpl->getBiasWeights();
1144 mImpl->setPrePadding(padding);
1154 return mImpl->getPrePadding();
1171 mImpl->setPostPadding(padding);
1181 return mImpl->getPostPadding();
1195 mImpl->setPaddingMode(paddingMode);
1207 return mImpl->getPaddingMode();
1220 mImpl->setKernelSizeNd(kernelSize);
1230 return mImpl->getKernelSizeNd();
1245 mImpl->setStrideNd(stride);
1255 return mImpl->getStrideNd();
1273 mImpl->setPaddingNd(padding);
1285 return mImpl->getPaddingNd();
1299 mImpl->setDilationNd(dilation);
1309 return mImpl->getDilationNd();
1358 mImpl->setActivationType(type);
1368 return mImpl->getActivationType();
1383 mImpl->setAlpha(alpha);
1397 mImpl->setBeta(beta);
1406 return mImpl->getAlpha();
1415 return mImpl->getBeta();
1445 static constexpr int32_t kVALUE = 3;
1472 mImpl->setPoolingType(type);
1482 return mImpl->getPoolingType();
1497 mImpl->setBlendFactor(blendFactor);
1510 return mImpl->getBlendFactor();
1524 mImpl->setAverageCountExcludesPadding(exclusive);
1535 return mImpl->getAverageCountExcludesPadding();
1553 mImpl->setPrePadding(padding);
1563 return mImpl->getPrePadding();
1581 mImpl->setPostPadding(padding);
1591 return mImpl->getPostPadding();
1604 mImpl->setPaddingMode(paddingMode);
1615 return mImpl->getPaddingMode();
1628 mImpl->setWindowSizeNd(windowSize);
1638 return mImpl->getWindowSizeNd();
1653 mImpl->setStrideNd(stride);
1663 return mImpl->getStrideNd();
1682 mImpl->setPaddingNd(padding);
1694 return mImpl->getPaddingNd();
1725 mImpl->setWindowSize(windowSize);
1735 return mImpl->getWindowSize();
1747 mImpl->setAlpha(alpha);
1757 return mImpl->getAlpha();
1769 mImpl->setBeta(beta);
1779 return mImpl->getBeta();
1801 return mImpl->getK();
1867 mImpl->setMode(mode);
1877 return mImpl->getMode();
1887 mImpl->setShift(shift);
1897 return mImpl->getShift();
1907 mImpl->setScale(scale);
1917 return mImpl->getScale();
1927 mImpl->setPower(power);
1937 return mImpl->getPower();
1952 return mImpl->getChannelAxis();
1973 mImpl->setChannelAxis(channelAxis);
2026 mImpl->setAxes(axes);
2036 return mImpl->getAxes();
2072 mImpl->setAxis(axis);
2082 return mImpl->getAxis();
2109 mImpl->setNbOutputMaps(nbOutputMaps);
2119 return mImpl->getNbOutputMaps();
2139 mImpl->setNbGroups(nbGroups);
2149 return mImpl->getNbGroups();
2163 mImpl->setKernelWeights(weights);
2173 return mImpl->getKernelWeights();
2188 mImpl->setBiasWeights(weights);
2198 return mImpl->getBiasWeights();
2215 mImpl->setPrePadding(padding);
2225 return mImpl->getPrePadding();
2242 mImpl->setPostPadding(padding);
2252 return mImpl->getPostPadding();
2266 mImpl->setPaddingMode(paddingMode);
2278 return mImpl->getPaddingMode();
2293 mImpl->setKernelSizeNd(kernelSize);
2303 return mImpl->getKernelSizeNd();
2320 mImpl->setStrideNd(stride);
2330 return mImpl->getStrideNd();
2348 mImpl->setPaddingNd(padding);
2360 return mImpl->getPaddingNd();
2386 mImpl->setDilationNd(dilation);
2396 return mImpl->getDilationNd();
2446 static constexpr int32_t kVALUE = 14;
2483 return mImpl->setOperation(op);
2495 return mImpl->getOperation();
2616 mImpl->setGatherAxis(axis);
2628 return mImpl->getGatherAxis();
2651 mImpl->setNbElementWiseDims(elementWiseDims);
2661 return mImpl->getNbElementWiseDims();
2671 mImpl->setMode(mode);
2681 return mImpl->getMode();
2710 return mImpl->getPlugin();
2737 return mImpl->getPlugin();
2820 mImpl->setOperation(op);
2830 return mImpl->getOperation();
2893 mImpl->setOperation(op);
2903 return mImpl->getOperation();
2913 mImpl->setReduceAxes(reduceAxes);
2923 return mImpl->getReduceAxes();
2933 mImpl->setKeepDimensions(keepDimensions);
2943 return mImpl->getKeepDimensions();
2977 mImpl->setPrePaddingNd(padding);
2989 return mImpl->getPrePaddingNd();
3003 mImpl->setPostPaddingNd(padding);
3015 return mImpl->getPostPaddingNd();
3065 mImpl->setFirstTranspose(permutation);
3077 return mImpl->getFirstTranspose();
3105 mImpl->setReshapeDimensions(dimensions);
3118 return mImpl->getReshapeDimensions();
3165 mImpl->setSecondTranspose(permutation);
3177 return mImpl->getSecondTranspose();
3193 return mImpl->setZeroIsPlaceholder(zeroIsPlaceholder);
3206 return mImpl->getZeroIsPlaceholder();
3317 mImpl->setStart(start);
3332 return mImpl->getStart();
3346 return mImpl->setSize(size);
3361 return mImpl->getSize();
3375 mImpl->setStride(stride);
3390 return mImpl->getStride();
3400 mImpl->setMode(mode);
3410 return mImpl->getMode();
3453 mImpl->setAxes(axes);
3468 return mImpl->getAxes();
3538 mImpl->setOperation(op);
3548 return mImpl->getOperation();
3576 return mImpl->getK();
3586 mImpl->setReduceAxes(reduceAxes);
3596 return mImpl->getReduceAxes();
3698 mImpl->setOperation(index, op);
3710 return mImpl->getOperation(index);
3818 mImpl->setToType(toType);
3829 return mImpl->getToType();
3858 mImpl->setWeights(weights);
3868 return mImpl->getWeights();
3880 mImpl->setDimensions(dimensions);
3892 return mImpl->getDimensions();
3938 static constexpr int32_t kVALUE = 3;
3992 static constexpr int32_t kVALUE = 3;
4022 static constexpr int32_t kVALUE = 2;
4058 static constexpr int32_t kVALUE = 4;
4121 return mImpl->setOutputDimensions(dimensions);
4131 return mImpl->getOutputDimensions();
4159 void setScales(
float const* scales, int32_t nbScales)
noexcept
4161 mImpl->setScales(scales, nbScales);
4178 int32_t
getScales(int32_t size,
float* scales)
const noexcept
4180 return mImpl->getScales(size, scales);
4192 mImpl->setResizeMode(interpolationMode);
4202 return mImpl->getResizeMode();
4237 mImpl->setCoordinateTransformation(coordTransform);
4247 return mImpl->getCoordinateTransformation();
4262 mImpl->setSelectorForSinglePixel(selector);
4272 return mImpl->getSelectorForSinglePixel();
4286 mImpl->setNearestRounding(value);
4296 return mImpl->getNearestRounding();
4318 mImpl->setCubicCoeff(A);
4328 return mImpl->getCubicCoeff();
4341 mImpl->setExcludeOutside(excludeFlag);
4351 return mImpl->getExcludeOutside();
4429 return mBoundary->getLoop();
4434 apiv::VLoopBoundaryLayer* mBoundary;
4452 return mBoundary->getConditional();
4457 apiv::VConditionalBoundaryLayer* mBoundary;
4540 return mImpl->setCondition(condition);
4558 return mImpl->addOutput(trueSubgraphOutput, falseSubgraphOutput);
4570 return mImpl->addInput(input);
4585 mImpl->setName(name);
4595 return mImpl->getName();
4665 return mImpl->getLoopOutput();
4682 mImpl->setAxis(axis);
4690 return mImpl->getAxis();
4739 return mImpl->getTripLimit();
4765 mImpl->setAxis(axis);
4773 return mImpl->getAxis();
4787 mImpl->setReverse(reverse);
4797 return mImpl->getReverse();
4825 return mImpl->addRecurrence(initialValue);
4846 return mImpl->addTripLimit(tensor, limit);
4859 return mImpl->addIterator(tensor, axis, reverse);
4872 return mImpl->addLoopOutput(tensor, outputKind, axis);
4887 mImpl->setName(name);
4897 return mImpl->getName();
4952 mImpl->setMessage(message);
4962 return mImpl->getMessage();
5064 mImpl->setDimensions(dimensions);
5079 return mImpl->getDimensions();
5089 mImpl->setOperation(op);
5099 return mImpl->getOperation();
5118 mImpl->setAlpha(alpha);
5133 return mImpl->getAlpha();
5152 mImpl->setBeta(beta);
5167 return mImpl->getBeta();
5228 mImpl->setAlphaInt64(alpha);
5243 return mImpl->getAlphaInt64();
5262 mImpl->setBetaInt64(beta);
5277 return mImpl->getBetaInt64();
5285 return mImpl->isAlphaBetaInt64();
5302 mImpl->setToType(toType);
5314 return mImpl->getToType();
5409 return mImpl->getAxis();
5420 mImpl->setAxis(axis);
5436 mImpl->setToType(toType);
5448 return mImpl->getToType();
5540 return mImpl->getAxis();
5551 mImpl->setAxis(axis);
5567 mImpl->setToType(toType);
5579 return mImpl->getToType();
5634 mImpl->setToType(toType);
5647 return mImpl->getToType();
5659 mImpl->setScaleType(scaleType);
5672 return mImpl->getScaleType();
5685 mImpl->setAxis(axis);
5695 return mImpl->getAxis();
5708 mImpl->setBlockSize(size);
5718 return mImpl->getBlockSize();
5776 return mImpl->setEquation(equation);
5786 return mImpl->getEquation();
5885 mImpl->setMode(mode);
5895 return mImpl->getMode();
5905 mImpl->setAxis(axis);
5913 return mImpl->getAxis();
5957 mImpl->setAxis(axis);
5965 return mImpl->getAxis();
5993 mImpl->setInterpolationMode(mode);
6005 return mImpl->getInterpolationMode();
6015 mImpl->setAlignCorners(alignCorners);
6027 return mImpl->getAlignCorners();
6039 return mImpl->setSampleMode(mode);
6051 return mImpl->getSampleMode();
6145 mImpl->setBoundingBoxFormat(fmt);
6157 return mImpl->getBoundingBoxFormat();
6171 mImpl->setTopKBoxLimit(limit);
6181 return mImpl->getTopKBoxLimit();
6234 mImpl->setBatchAxis(batchAxis);
6244 return mImpl->getBatchAxis();
6257 mImpl->setSequenceAxis(sequenceAxis);
6267 return mImpl->getSequenceAxis();
6305 return mImpl->setEpsilon(eps);
6315 return mImpl->getEpsilon();
6325 return mImpl->setAxes(axesMask);
6335 return mImpl->getAxes();
6356 return mImpl->setNbGroups(nbGroups);
6366 return mImpl->getNbGroups();
6392 return mImpl->setComputePrecision(type);
6402 return mImpl->getComputePrecision();
6496 static constexpr int32_t kVALUE = 1;
6542 return mImpl->setOperation(op);
6554 return mImpl->getOperation();
6566 mImpl->setExclusive(exclusive);
6578 return mImpl->getExclusive();
6590 mImpl->setReverse(reverse);
6602 return mImpl->getReverse();
6670 return mImpl->addInput(name, type, dimensions);
6684 mImpl->markOutput(tensor);
6702 return mImpl->markDebug(tensor);
6718 return mImpl->unmarkDebug(tensor);
6728 return mImpl->isDebugTensor(tensor);
6748 return mImpl->addActivation(input, type);
6767 return mImpl->addLRN(input, window, alpha, beta, k);
6793 return mImpl->addScale(input, mode, shift, scale, power);
6806 return mImpl->addSoftMax(input);
6823 return mImpl->addConcatenation(inputs, nbInputs);
6850 return mImpl->addElementWise(input1, input2, op);
6872 return mImpl->addUnary(input, operation);
6886 return mImpl->addShuffle(input);
6903 return mImpl->addOneHot(indices, values, depth, axis);
6915 return mImpl->getNbLayers();
6929 return mImpl->getLayer(index);
6941 return mImpl->getNbInputs();
6957 return mImpl->getInput(index);
6971 return mImpl->getNbOutputs();
6987 return mImpl->getOutput(index);
7014 return mImpl->addReduce(input, operation, reduceAxes, keepDimensions);
7046 return mImpl->addTopK(input, op, k, reduceAxes);
7062 return mImpl->addGather(data, indices, axis);
7078 return mImpl->addGatherV2(data, indices, mode);
7097 return mImpl->addRaggedSoftMax(input, bounds);
7119 return mImpl->addMatrixMultiply(input0, op0, input1, op1);
7133 return mImpl->addNonZero(input);
7157 return mImpl->addConstant(dimensions, weights);
7171 return mImpl->addIdentity(input);
7186 return mImpl->addCast(input, toType);
7201 mImpl->removeTensor(tensor);
7213 mImpl->unmarkOutput(tensor);
7234 return mImpl->addPluginV2(inputs, nbInputs, plugin);
7251 int32_t nbShapeInputs,
IPluginV3& plugin)
noexcept
7253 return mImpl->addPluginV3(inputs, nbInputs, shapeInputs, nbShapeInputs, plugin);
7272 return mImpl->addSlice(input, start, size, stride);
7296 mImpl->setName(name);
7310 return mImpl->getName();
7326 return mImpl->addShape(input);
7340 return mImpl->hasImplicitBatchDimension();
7350 return mImpl->getFlags();
7362 return mImpl->getFlag(networkDefinitionCreationFlag);
7379 return mImpl->markOutputForShapes(tensor);
7391 return mImpl->unmarkOutputForShapes(tensor);
7409 return mImpl->addParametricReLU(input, slope);
7432 return mImpl->addConvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7451 return mImpl->addPoolingNd(input, type, windowSize);
7474 return mImpl->addDeconvolutionNd(input, nbOutputMaps, kernelSize, kernelWeights, biasWeights);
7511 return mImpl->addScaleNd(input, mode, shift, scale, power, channelAxis);
7527 return mImpl->addResize(input);
7541 return mImpl->addLoop();
7556 return mImpl->addIfConditional();
7595 return mImpl->addSelect(condition, thenInput, elseInput);
7612 return mImpl->addAssertion(condition, message);
7637 return mImpl->addFill(dimensions, op);
7663 return mImpl->addFillV2(dimensions, op, outputType);
7679 return mImpl->addPaddingNd(input, prePadding, postPadding);
7703 return mImpl->setWeightsName(weights, name);
7722 mImpl->setErrorRecorder(recorder);
7737 return mImpl->getErrorRecorder();
7758 return mImpl->addDequantize(input, scale);
7779 return mImpl->addDequantizeV2(input, scale, outputType);
7799 return mImpl->addScatter(data, indices, updates, mode);
7820 return mImpl->addQuantize(input, scale);
7841 return mImpl->addQuantizeV2(input, scale, outputType);
7868 return mImpl->addDynamicQuantize(input, axis, blockSize, outputType, scaleType);
7883 return mImpl->addEinsum(inputs, nbInputs, equation);
7901 return mImpl->addGridSample(input, grid);
7919 return mImpl->addNMS(boxes, scores, maxOutputBoxesPerClass);
7936 return mImpl->addReverseSequence(input, sequenceLens);
7962 return mImpl->addNormalization(input, scale, bias, axesMask);
7984 return mImpl->addCumulative(input, axis, operation, exclusive, reverse);
7995 return mImpl->getBuilder();
8008 return mImpl->markWeightsRefittable(name);
8020 return mImpl->unmarkWeightsRefittable(name);
8033 return mImpl->areWeightsMarkedRefittable(name);
8052 return mImpl->addSqueeze(input, axes);
8073 return mImpl->addUnsqueeze(input, axes);
8145 virtual
bool getBatch(
void* bindings[],
char const* names[], int32_t nbBindings) noexcept = 0;
8161 virtual
void const* readCalibrationCache(std::
size_t& length) noexcept = 0;
8171 virtual
void writeCalibrationCache(
void const* ptr, std::
size_t length) noexcept = 0;
8337 virtual
double getRegressionCutoff() const noexcept = 0;
8351 virtual
void const* readHistogramCache(std::
size_t& length) noexcept = 0;
8361 virtual
void writeHistogramCache(
void const* ptr, std::
size_t length) noexcept = 0;
8404 return mImpl->getDataType();
8415 return mImpl->getStrides();
8425 return mImpl->getVectorizedDim();
8436 return mImpl->getComponentsPerElement();
8465 return mImpl->getImplementation();
8473 return mImpl->getTactic();
8501 return mImpl->getName();
8513 return mImpl->getDimensions(index, select);
8521 return mImpl->getNbInputs();
8529 return mImpl->getNbOutputs();
8558 return mImpl->getAlgorithmVariant();
8566 return mImpl->getTimingMSec();
8574 return mImpl->getWorkspaceSize();
8588 return mImpl->getAlgorithmIOInfoByIndex(index);
8623 int32_t nbChoices, int32_t* selection)
noexcept = 0;
8636 int32_t nbAlgorithms)
noexcept = 0;
8730 static constexpr int32_t kVALUE = 2;
8949 static constexpr uint64_t kINVALID_TACTIC_HASH = UINT64_MAX;
8982 return mImpl->serialize();
9006 return mImpl->combine(inputCache, ignoreMismatch);
9016 return mImpl->reset();
9033 int64_t
queryKeys(TimingCacheKey* keyBuffer, int64_t capacity)
const noexcept
9035 return mImpl->queryKeys(keyBuffer, capacity);
9050 TimingCacheValue
query(TimingCacheKey
const& key)
const noexcept
9052 return mImpl->query(key);
9072 bool update(TimingCacheKey
const& key, TimingCacheValue
const& value)
noexcept
9074 return mImpl->update(key, value);
9188 static constexpr int32_t kVALUE = 2;
9230 static constexpr int32_t kVALUE = 2;
9269 static constexpr int32_t kVALUE = 4;
9308 virtual void phaseStart(
char const* phaseName,
char const* parentPhase, int32_t nbSteps)
noexcept = 0;
9322 virtual bool stepComplete(
char const* phaseName, int32_t step)
noexcept = 0;
9381 virtual
void setAvgTimingIterations(int32_t avgTiming) noexcept
9383 mImpl->setAvgTimingIterations(avgTiming);
9395 return mImpl->getAvgTimingIterations();
9408 mImpl->setEngineCapability(capability);
9420 return mImpl->getEngineCapability();
9432 mImpl->setInt8Calibrator(calibrator);
9442 return mImpl->getInt8Calibrator();
9459 mImpl->setFlags(builderFlags);
9471 return mImpl->getFlags();
9483 mImpl->clearFlag(builderFlag);
9495 mImpl->setFlag(builderFlag);
9507 return mImpl->getFlag(builderFlag);
9524 mImpl->setDeviceType(layer, deviceType);
9534 return mImpl->getDeviceType(layer);
9546 return mImpl->isDeviceTypeSet(layer);
9556 mImpl->resetDeviceType(layer);
9566 return mImpl->canRunOnDLA(layer);
9582 mImpl->setDLACore(dlaCore);
9592 return mImpl->getDLACore();
9603 mImpl->setDefaultDeviceType(deviceType);
9613 return mImpl->getDefaultDeviceType();
9635 return mImpl->setProfileStream(stream);
9647 return mImpl->getProfileStream();
9664 return mImpl->addOptimizationProfile(profile);
9677 return mImpl->getNbOptimizationProfiles();
9689 mImpl->setProfilingVerbosity(verbosity);
9702 return mImpl->getProfilingVerbosity();
9714 mImpl->setAlgorithmSelector(selector);
9724 return mImpl->getAlgorithmSelector();
9742 return mImpl->setCalibrationProfile(profile);
9754 return mImpl->getCalibrationProfile();
9771 mImpl->setQuantizationFlags(flags);
9783 return mImpl->getQuantizationFlags();
9795 mImpl->clearQuantizationFlag(flag);
9807 mImpl->setQuantizationFlag(flag);
9819 return mImpl->getQuantizationFlag(flag);
9841 return mImpl->setTacticSources(tacticSources);
9856 return mImpl->getTacticSources();
9875 return mImpl->createTimingCache(blob, size);
9898 return mImpl->setTimingCache(cache, ignoreMismatch);
9908 return mImpl->getTimingCache();
9940 mImpl->setMemoryPoolLimit(pool, poolSize);
9959 return mImpl->getMemoryPoolLimit(pool);
9977 mImpl->setPreviewFeature(feature, enable);
9991 return mImpl->getPreviewFeature(feature);
10024 mImpl->setBuilderOptimizationLevel(level);
10036 return mImpl->getBuilderOptimizationLevel();
10053 mImpl->setHardwareCompatibilityLevel(hardwareCompatibilityLevel);
10066 return mImpl->getHardwareCompatibilityLevel();
10079 mImpl->setPluginsToSerialize(paths, nbPaths);
10092 return mImpl->getPluginToSerialize(index);
10102 return mImpl->getNbPluginsToSerialize();
10131 mImpl->setMaxAuxStreams(nbStreams);
10141 return mImpl->getMaxAuxStreams();
10157 return mImpl->setProgressMonitor(monitor);
10167 return mImpl->getProgressMonitor();
10183 mImpl->setRuntimePlatform(runtimePlatform);
10195 return mImpl->getRuntimePlatform();
10207 mImpl->setMaxNbTactics(maxNbTactics);
10219 return mImpl->getMaxNbTactics();
10235 return mImpl->setTilingOptimizationLevel(level);
10247 return mImpl->getTilingOptimizationLevel();
10263 return mImpl->setL2LimitForTiling(size);
10275 return mImpl->getL2LimitForTiling();
10343 return mImpl->platformHasFastFp16();
10353 return mImpl->platformHasFastInt8();
10365 return mImpl->getMaxDLABatchSize();
10373 return mImpl->getNbDLACores();
10390 mImpl->setGpuAllocator(allocator);
10400 return mImpl->createBuilderConfig();
10422 return mImpl->createNetworkV2(flags);
10437 return mImpl->createOptimizationProfile();
10456 mImpl->setErrorRecorder(recorder);
10471 return mImpl->getErrorRecorder();
10489 return mImpl->platformHasTf32();
10508 return mImpl->buildSerializedNetwork(network, config);
10528 return mImpl->buildEngineWithConfig(network, config);
10550 return mImpl->isNetworkSupported(network, config);
10560 return mImpl->getLogger();
10576 return mImpl->setMaxThreads(maxThreads);
10590 return mImpl->getMaxThreads();
10600 return mImpl->getPluginRegistry();
10613extern "C" TENSORRTAPI void* createInferBuilder_INTERNAL(
void* logger, int32_t version)
noexcept;
#define TENSORRTAPI
Definition: NvInferRuntimeBase.h:59
#define NV_TENSORRT_VERSION
Definition: NvInferRuntimeBase.h:91
#define TRT_DEPRECATED
Definition: NvInferRuntimeBase.h:45
#define TRT_DEPRECATED_ENUM
Definition: NvInferRuntimeBase.h:46
Definition: NvInferRuntimeBase.h:203
static constexpr int32_t MAX_DIMS
The maximum rank (number of dimensions) supported for a tensor.
Definition: NvInferRuntimeBase.h:206
An Activation layer in a network definition.
Definition: NvInfer.h:1347
void setBeta(float beta) noexcept
Set the beta parameter (must be finite).
Definition: NvInfer.h:1395
void setActivationType(ActivationType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1356
ActivationType getActivationType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1366
float getAlpha() const noexcept
Get the alpha parameter.
Definition: NvInfer.h:1404
virtual ~IActivationLayer() noexcept=default
float getBeta() const noexcept
Get the beta parameter.
Definition: NvInfer.h:1413
void setAlpha(float alpha) noexcept
Set the alpha parameter (must be finite).
Definition: NvInfer.h:1381
Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorith...
Definition: NvInfer.h:8492
int32_t getNbOutputs() const noexcept
Return number of outputs of the algorithm.
Definition: NvInfer.h:8527
int32_t getNbInputs() const noexcept
Return number of inputs of the algorithm.
Definition: NvInfer.h:8519
char const * getName() const noexcept
Return name of the algorithm node.
Definition: NvInfer.h:8499
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:8511
Describes a variation of execution of a layer. An algorithm is represented by IAlgorithmVariant and t...
Definition: NvInfer.h:8551
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:8572
float getTimingMSec() const noexcept
The time in milliseconds to execute the algorithm.
Definition: NvInfer.h:8564
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:8586
virtual ~IAlgorithm() noexcept=default
IAlgorithmVariant const & getAlgorithmVariant() const noexcept
Returns the algorithm variant.
Definition: NvInfer.h:8556
Carries information about input or output of the algorithm. IAlgorithmIOInfo for all the input and ou...
Definition: NvInfer.h:8395
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:8423
Dims getStrides() const noexcept
Return strides of the input/output tensor of algorithm. For vectorized formats, strides are given in ...
Definition: NvInfer.h:8413
DataType getDataType() const noexcept
Return DataType of the input/output of algorithm.
Definition: NvInfer.h:8402
int64_t getComponentsPerElement() const noexcept
Return the number of components per element. This is always 1 for non-vectorized formats.
Definition: NvInfer.h:8434
provides a unique 128-bit identifier, which along with the input and output information denotes the v...
Definition: NvInfer.h:8458
virtual ~IAlgorithmVariant() noexcept=default
int64_t getTactic() const noexcept
Return tactic of the algorithm.
Definition: NvInfer.h:8471
int64_t getImplementation() const noexcept
Return implementation of the algorithm.
Definition: NvInfer.h:8463
An assertion layer in a network.
Definition: NvInfer.h:4940
void setMessage(char const *message) noexcept
Set the message to print if the assertion fails.
Definition: NvInfer.h:4950
char const * getMessage() const noexcept
Return the assertion message.
Definition: NvInfer.h:4960
virtual ~IAssertionLayer() noexcept=default
Holds properties for configuring a builder to produce an engine.
Definition: NvInfer.h:9369
void setMemoryPoolLimit(MemoryPoolType pool, std::size_t poolSize) noexcept
Set the memory size for the memory pool.
Definition: NvInfer.h:9938
void setQuantizationFlag(QuantizationFlag flag) noexcept
Set a single quantization flag.
Definition: NvInfer.h:9805
nvinfer1::ITimingCache * createTimingCache(void const *blob, std::size_t size) const noexcept
Create timing cache.
Definition: NvInfer.h:9873
void setPreviewFeature(PreviewFeature feature, bool enable) noexcept
Enable or disable a specific preview feature.
Definition: NvInfer.h:9975
TRT_DEPRECATED void setAlgorithmSelector(IAlgorithmSelector *selector) noexcept
Set Algorithm Selector.
Definition: NvInfer.h:9712
TRT_DEPRECATED void setInt8Calibrator(IInt8Calibrator *calibrator) noexcept
Set Int8 Calibration interface.
Definition: NvInfer.h:9430
bool getPreviewFeature(PreviewFeature feature) const noexcept
Get status of preview feature.
Definition: NvInfer.h:9989
void clearQuantizationFlag(QuantizationFlag flag) noexcept
clear a quantization flag.
Definition: NvInfer.h:9793
int32_t getBuilderOptimizationLevel() noexcept
Get builder optimization level.
Definition: NvInfer.h:10034
bool setTacticSources(TacticSources tacticSources) noexcept
Set tactic sources.
Definition: NvInfer.h:9839
void setPluginsToSerialize(char const *const *paths, int32_t nbPaths) noexcept
Set the plugin libraries to be serialized with version-compatible engines.
Definition: NvInfer.h:10077
bool setTilingOptimizationLevel(TilingOptimizationLevel level) noexcept
Set the Tiling optimization level.
Definition: NvInfer.h:10233
bool setL2LimitForTiling(int64_t size) noexcept
Set the L2 cache usage limit for Tiling optimization.
Definition: NvInfer.h:10261
bool getQuantizationFlag(QuantizationFlag flag) const noexcept
Returns true if the quantization flag is set.
Definition: NvInfer.h:9817
TRT_DEPRECATED IInt8Calibrator * getInt8Calibrator() const noexcept
Get Int8 Calibration interface.
Definition: NvInfer.h:9440
std::size_t getMemoryPoolLimit(MemoryPoolType pool) const noexcept
Get the memory size limit of the memory pool.
Definition: NvInfer.h:9957
int32_t getDLACore() const noexcept
Get the DLA core that the engine executes on.
Definition: NvInfer.h:9590
int32_t getNbPluginsToSerialize() const noexcept
Get the number of plugin library paths to be serialized with version-compatible engines.
Definition: NvInfer.h:10100
void setDeviceType(ILayer const *layer, DeviceType deviceType) noexcept
Set the device that this layer must execute on.
Definition: NvInfer.h:9522
void setEngineCapability(EngineCapability capability) noexcept
Configure the builder to target specified EngineCapability flow.
Definition: NvInfer.h:9406
int32_t getMaxAuxStreams() const noexcept
Get the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:10139
bool getFlag(BuilderFlag builderFlag) const noexcept
Returns true if the build mode flag is set.
Definition: NvInfer.h:9505
void setQuantizationFlags(QuantizationFlags flags) noexcept
Set the quantization flags.
Definition: NvInfer.h:9769
void setMaxNbTactics(int32_t maxNbTactics) noexcept
Set the maximum number of tactics to time when there is a choice of tactics.
Definition: NvInfer.h:10205
int64_t getL2LimitForTiling() const noexcept
Get the L2 cache usage limit for tiling optimization.
Definition: NvInfer.h:10273
void setProgressMonitor(IProgressMonitor *monitor) noexcept
Sets the progress monitor for building a network.
Definition: NvInfer.h:10155
void setProfilingVerbosity(ProfilingVerbosity verbosity) noexcept
Set verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:9687
int32_t getNbOptimizationProfiles() const noexcept
Get number of optimization profiles.
Definition: NvInfer.h:9675
QuantizationFlags getQuantizationFlags() const noexcept
Get the quantization flags.
Definition: NvInfer.h:9781
nvinfer1::ITimingCache const * getTimingCache() const noexcept
Get the pointer to the timing cache from current IBuilderConfig.
Definition: NvInfer.h:9906
void reset() noexcept
Resets the builder configuration to defaults.
Definition: NvInfer.h:9621
bool setTimingCache(ITimingCache const &cache, bool ignoreMismatch) noexcept
Attach a timing cache to IBuilderConfig.
Definition: NvInfer.h:9896
char const * getPluginToSerialize(int32_t index) const noexcept
Get the plugin library path to be serialized with version-compatible engines.
Definition: NvInfer.h:10090
EngineCapability getEngineCapability() const noexcept
Query EngineCapability flow configured for the builder.
Definition: NvInfer.h:9418
RuntimePlatform getRuntimePlatform() const noexcept
Get the target platform for runtime execution.
Definition: NvInfer.h:10193
DeviceType getDefaultDeviceType() const noexcept
Get the default DeviceType which was set by setDefaultDeviceType.
Definition: NvInfer.h:9611
void setRuntimePlatform(RuntimePlatform runtimePlatform) noexcept
Set the target platform for runtime execution.
Definition: NvInfer.h:10181
int32_t getMaxNbTactics() const noexcept
Query the maximum number of tactics timed when there is a choice.
Definition: NvInfer.h:10217
BuilderFlags getFlags() const noexcept
Get the build mode flags for this builder config. Defaults to 0.
Definition: NvInfer.h:9469
void setFlags(BuilderFlags builderFlags) noexcept
Set the build mode flags to turn on builder options for this network.
Definition: NvInfer.h:9457
TacticSources getTacticSources() const noexcept
Get tactic sources.
Definition: NvInfer.h:9854
void resetDeviceType(ILayer const *layer) noexcept
reset the DeviceType for this layer
Definition: NvInfer.h:9554
void setDLACore(int32_t dlaCore) noexcept
Sets the DLA core used by the network. Defaults to -1.
Definition: NvInfer.h:9580
HardwareCompatibilityLevel getHardwareCompatibilityLevel() const noexcept
Get the hardware compatibility level.
Definition: NvInfer.h:10064
void clearFlag(BuilderFlag builderFlag) noexcept
clear a single build mode flag.
Definition: NvInfer.h:9481
int32_t addOptimizationProfile(IOptimizationProfile const *profile) noexcept
Add an optimization profile.
Definition: NvInfer.h:9662
IProgressMonitor * getProgressMonitor() const noexcept
Definition: NvInfer.h:10165
apiv::VBuilderConfig * mImpl
Definition: NvInfer.h:10279
TRT_DEPRECATED IOptimizationProfile const * getCalibrationProfile() noexcept
Get the current calibration profile.
Definition: NvInfer.h:9752
int32_t getAvgTimingIterations() const noexcept
Query the number of averaging iterations.
Definition: NvInfer.h:9393
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:9601
void setFlag(BuilderFlag builderFlag) noexcept
Set a single build mode flag.
Definition: NvInfer.h:9493
TRT_DEPRECATED bool setCalibrationProfile(IOptimizationProfile const *profile) noexcept
Add a calibration profile.
Definition: NvInfer.h:9740
virtual ~IBuilderConfig() noexcept=default
DeviceType getDeviceType(ILayer const *layer) const noexcept
Get the device that this layer executes on.
Definition: NvInfer.h:9532
bool canRunOnDLA(ILayer const *layer) const noexcept
Checks if a layer can run on DLA.
Definition: NvInfer.h:9564
cudaStream_t getProfileStream() const noexcept
Get the CUDA stream that is used to profile this network.
Definition: NvInfer.h:9645
void setHardwareCompatibilityLevel(HardwareCompatibilityLevel hardwareCompatibilityLevel) noexcept
Set the hardware compatibility level.
Definition: NvInfer.h:10051
TilingOptimizationLevel getTilingOptimizationLevel() const noexcept
Get the Tiling optimization level.
Definition: NvInfer.h:10245
void setMaxAuxStreams(int32_t nbStreams) noexcept
Set the maximum number of auxiliary streams that TRT is allowed to use.
Definition: NvInfer.h:10129
ProfilingVerbosity getProfilingVerbosity() const noexcept
Get verbosity level of layer information exposed in NVTX annotations and IEngineInspector.
Definition: NvInfer.h:9700
bool isDeviceTypeSet(ILayer const *layer) const noexcept
whether the DeviceType has been explicitly set for this layer
Definition: NvInfer.h:9544
void setBuilderOptimizationLevel(int32_t level) noexcept
Set builder optimization level.
Definition: NvInfer.h:10022
void setProfileStream(const cudaStream_t stream) noexcept
Set the CUDA stream that is used to profile this network.
Definition: NvInfer.h:9633
TRT_DEPRECATED IAlgorithmSelector * getAlgorithmSelector() const noexcept
Get Algorithm Selector.
Definition: NvInfer.h:9722
Builds an engine from a network definition.
Definition: NvInfer.h:10332
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:10363
int32_t getNbDLACores() const noexcept
Return the number of DLA engines available to this builder.
Definition: NvInfer.h:10371
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:10469
apiv::VBuilder * mImpl
Definition: NvInfer.h:10604
ILogger * getLogger() const noexcept
get the logger with which the builder was created
Definition: NvInfer.h:10558
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:10548
int32_t getMaxThreads() const noexcept
get the maximum number of threads that can be used by the builder.
Definition: NvInfer.h:10588
IPluginRegistry & getPluginRegistry() noexcept
get the local plugin registry that can be used by the builder.
Definition: NvInfer.h:10598
TRT_DEPRECATED bool platformHasFastInt8() const noexcept
Determine whether the platform has fast native int8.
Definition: NvInfer.h:10351
nvinfer1::IOptimizationProfile * createOptimizationProfile() noexcept
Create a new optimization profile.
Definition: NvInfer.h:10435
void setGpuAllocator(IGpuAllocator *allocator) noexcept
Set the GPU allocator.
Definition: NvInfer.h:10388
nvinfer1::INetworkDefinition * createNetworkV2(NetworkDefinitionCreationFlags flags) noexcept
Create a network definition object.
Definition: NvInfer.h:10420
nvinfer1::IBuilderConfig * createBuilderConfig() noexcept
Create a builder configuration object.
Definition: NvInfer.h:10398
void reset() noexcept
Resets the builder state to default values.
Definition: NvInfer.h:10477
bool setMaxThreads(int32_t maxThreads) noexcept
Set the maximum number of threads.
Definition: NvInfer.h:10574
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:10454
nvinfer1::IHostMemory * buildSerializedNetwork(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds and serializes a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:10506
virtual ~IBuilder() noexcept=default
TRT_DEPRECATED bool platformHasTf32() const noexcept
Determine whether the platform has TF32 support.
Definition: NvInfer.h:10487
nvinfer1::ICudaEngine * buildEngineWithConfig(INetworkDefinition &network, IBuilderConfig &config) noexcept
Builds a network for the given INetworkDefinition and IBuilderConfig.
Definition: NvInfer.h:10526
A cast layer in a network.
Definition: NvInfer.h:3807
virtual ~ICastLayer() noexcept=default
apiv::VCastLayer * mImpl
Definition: NvInfer.h:3833
DataType getToType() const noexcept
Return cast layer output type.
Definition: NvInfer.h:3827
void setToType(DataType toType) noexcept
Set cast layer output type.
Definition: NvInfer.h:3816
A concatenation layer in a network definition.
Definition: NvInfer.h:2057
void setAxis(int32_t axis) noexcept
Set the axis along which concatenation occurs.
Definition: NvInfer.h:2070
int32_t getAxis() const noexcept
Get the axis along which concatenation occurs.
Definition: NvInfer.h:2080
virtual ~IConcatenationLayer() noexcept=default
This layer represents a condition input to an IIfConditional.
Definition: NvInfer.h:4466
virtual ~IConditionLayer() noexcept=default
Layer that represents a constant value.
Definition: NvInfer.h:3846
void setWeights(Weights weights) noexcept
Set the weights for the layer.
Definition: NvInfer.h:3856
Weights getWeights() const noexcept
Get the weights for the layer.
Definition: NvInfer.h:3866
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions for the layer.
Definition: NvInfer.h:3878
apiv::VConstantLayer * mImpl
Definition: NvInfer.h:3896
virtual ~IConstantLayer() noexcept=default
Dims getDimensions() const noexcept
Get the dimensions for the layer.
Definition: NvInfer.h:3890
A convolution layer in a network definition.
Definition: NvInfer.h:1027
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1152
Weights getBiasWeights() const noexcept
Get the bias weights for the convolution.
Definition: NvInfer.h:1125
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1193
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1297
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the convolution.
Definition: NvInfer.h:1283
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the convolution.
Definition: NvInfer.h:1253
Weights getKernelWeights() const noexcept
Get the kernel weights of the convolution.
Definition: NvInfer.h:1100
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the convolution.
Definition: NvInfer.h:1243
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the convolution.
Definition: NvInfer.h:1307
int64_t getNbOutputMaps() const noexcept
Get the number of output maps for the convolution.
Definition: NvInfer.h:1046
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the convolution.
Definition: NvInfer.h:1090
Dims getPostPadding() const noexcept
Get the post-padding.
Definition: NvInfer.h:1179
int64_t getNbGroups() const noexcept
Get the number of groups of the convolution.
Definition: NvInfer.h:1076
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1205
virtual ~IConvolutionLayer() noexcept=default
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a convolution.
Definition: NvInfer.h:1066
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output maps for the convolution.
Definition: NvInfer.h:1036
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the convolution.
Definition: NvInfer.h:1115
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1228
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the convolution.
Definition: NvInfer.h:1271
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the convolution.
Definition: NvInfer.h:1142
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the convolution.
Definition: NvInfer.h:1169
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the convolution.
Definition: NvInfer.h:1218
An engine for executing inference on a built network, with functionally unsafe features.
Definition: NvInferRuntime.h:3002
Layer that represents a cumulative operation across a tensor.
Definition: NvInfer.h:6529
bool setOperation(CumulativeOperation op) noexcept
Set the cumulative operation for the layer.
Definition: NvInfer.h:6540
void setReverse(bool reverse) noexcept
Specify whether the cumulative operation should be applied backward.
Definition: NvInfer.h:6588
apiv::VCumulativeLayer * mImpl
Definition: NvInfer.h:6606
bool getExclusive() const noexcept
Get whether it is exclusive accumulation or inclusive accumulation.
Definition: NvInfer.h:6576
virtual ~ICumulativeLayer() noexcept=default
bool getReverse() const noexcept
Get the boolean that specifies whether the cumulative operation should be applied backward.
Definition: NvInfer.h:6600
void setExclusive(bool exclusive) noexcept
Set whether it is an exclusive accumulation or inclusive accumulation.
Definition: NvInfer.h:6564
CumulativeOperation getOperation() const noexcept
Get the cumulative operation for the layer.
Definition: NvInfer.h:6552
A deconvolution layer in a network definition.
Definition: NvInfer.h:2098
void setBiasWeights(Weights weights) noexcept
Set the bias weights for the deconvolution.
Definition: NvInfer.h:2186
int64_t getNbGroups() const noexcept
Get the number of groups for a deconvolution.
Definition: NvInfer.h:2147
Weights getKernelWeights() const noexcept
Get the kernel weights for the deconvolution.
Definition: NvInfer.h:2171
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding of the deconvolution.
Definition: NvInfer.h:2213
Dims getStrideNd() const noexcept
Get the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2328
Dims getDilationNd() const noexcept
Get the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2394
Weights getBiasWeights() const noexcept
Get the bias weights for the deconvolution.
Definition: NvInfer.h:2196
void setKernelWeights(Weights weights) noexcept
Set the kernel weights for the deconvolution.
Definition: NvInfer.h:2161
int64_t getNbOutputMaps() const noexcept
Get the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2117
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride of the deconvolution.
Definition: NvInfer.h:2318
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:2250
Dims getKernelSizeNd() const noexcept
Get the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2301
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding of the deconvolution.
Definition: NvInfer.h:2240
void setKernelSizeNd(Dims const &kernelSize) noexcept
Set the multi-dimension kernel size of the deconvolution.
Definition: NvInfer.h:2291
virtual ~IDeconvolutionLayer() noexcept=default
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2346
void setNbOutputMaps(int64_t nbOutputMaps) noexcept
Set the number of output feature maps for the deconvolution.
Definition: NvInfer.h:2107
Dims getPaddingNd() const noexcept
Get the multi-dimension padding of the deconvolution.
Definition: NvInfer.h:2358
void setDilationNd(Dims const &dilation) noexcept
Set the multi-dimension dilation of the deconvolution.
Definition: NvInfer.h:2384
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:2264
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups for a deconvolution.
Definition: NvInfer.h:2137
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:2223
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:2276
A Dequantize layer in a network definition.
Definition: NvInfer.h:5528
void setToType(DataType toType) noexcept
Set the Dequantize layer output type.
Definition: NvInfer.h:5565
virtual ~IDequantizeLayer() noexcept=default
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5538
DataType getToType() const noexcept
Return the Dequantize layer output type.
Definition: NvInfer.h:5577
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5549
A network layer to perform dynamic quantization.
Definition: NvInfer.h:5605
int32_t getAxis() const noexcept
Get the axis along which blocking occurs.
Definition: NvInfer.h:5693
int32_t getBlockSize() const noexcept
Get the size of the quantization block.
Definition: NvInfer.h:5716
DataType getScaleType() const noexcept
Return the scale factors data type.
Definition: NvInfer.h:5670
void setScaleType(DataType scaleType) noexcept
Set the data type of the scale factors used to quantize the data.
Definition: NvInfer.h:5657
DataType getToType() const noexcept
Return DynamicQuantizeLayer’s quantized output type.
Definition: NvInfer.h:5645
virtual ~IDynamicQuantizeLayer() noexcept=default
void setToType(DataType toType) noexcept
Set DynamicQuantizeLayer’s quantized output type.
Definition: NvInfer.h:5632
void setAxis(int32_t axis) noexcept
Set the axis along which block quantization occurs.
Definition: NvInfer.h:5683
void setBlockSize(int32_t size) noexcept
Set the size of the quantization block.
Definition: NvInfer.h:5706
An Einsum layer in a network.
Definition: NvInfer.h:5763
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:5774
virtual ~IEinsumLayer() noexcept=default
char const * getEquation() const noexcept
Return the equation.
Definition: NvInfer.h:5784
A elementwise layer in a network definition.
Definition: NvInfer.h:2470
virtual ~IElementWiseLayer() noexcept=default
apiv::VElementWiseLayer * mImpl
Definition: NvInfer.h:2499
ElementWiseOperation getOperation() const noexcept
Get the binary operation for the layer.
Definition: NvInfer.h:2493
void setOperation(ElementWiseOperation op) noexcept
Set the binary operation for the layer.
Definition: NvInfer.h:2481
Generate a tensor according to a specified mode.
Definition: NvInfer.h:5051
bool isAlphaBetaInt64() const noexcept
Return true if alpha/beta have type int64, false if they have type double.
Definition: NvInfer.h:5283
FillOperation getOperation() const noexcept
Get the fill operation for the layer.
Definition: NvInfer.h:5097
void setOperation(FillOperation op) noexcept
Set the fill operation for the layer.
Definition: NvInfer.h:5087
DataType getToType() const noexcept
Get the fill layer output type.
Definition: NvInfer.h:5312
void setAlphaInt64(int64_t alpha) noexcept
Set the alpha parameter with int64 datatype.
Definition: NvInfer.h:5226
void setBetaInt64(int64_t beta) noexcept
Set the beta parameter with int64 datatype.
Definition: NvInfer.h:5260
void setBeta(double beta) noexcept
Set the beta parameter.
Definition: NvInfer.h:5150
int64_t getAlphaInt64() const noexcept
Get the value of alpha parameter with int64 datatype.
Definition: NvInfer.h:5241
int64_t getBetaInt64() const noexcept
Get the value of beta parameter with int64 datatype.
Definition: NvInfer.h:5275
double getAlpha() const noexcept
Get the value of alpha parameter.
Definition: NvInfer.h:5131
void setDimensions(Dims const &dimensions) noexcept
Set the output tensor's dimensions.
Definition: NvInfer.h:5062
void setAlpha(double alpha) noexcept
Set the alpha parameter.
Definition: NvInfer.h:5116
void setToType(DataType toType) noexcept
Set the fill layer output type.
Definition: NvInfer.h:5300
Dims getDimensions() const noexcept
Get the output tensor's dimensions.
Definition: NvInfer.h:5077
double getBeta() const noexcept
Get the value of beta parameter.
Definition: NvInfer.h:5165
virtual ~IFillLayer() noexcept=default
A Gather layer in a network definition. Supports several kinds of gathering.
Definition: NvInfer.h:2603
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:2614
void setNbElementWiseDims(int32_t elementWiseDims) noexcept
Set the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2649
apiv::VGatherLayer * mImpl
Definition: NvInfer.h:2685
int32_t getNbElementWiseDims() const noexcept
Get the number of leading dimensions of indices tensor to be handled elementwise.
Definition: NvInfer.h:2659
void setMode(GatherMode mode) noexcept
Set the gather mode.
Definition: NvInfer.h:2669
int32_t getGatherAxis() const noexcept
Get the axis to gather on.
Definition: NvInfer.h:2626
GatherMode getMode() const noexcept
Get the gather mode.
Definition: NvInfer.h:2679
virtual ~IGatherLayer() noexcept=default
A GridSample layer in a network definition.
Definition: NvInfer.h:5984
void setInterpolationMode(InterpolationMode mode) noexcept
Set the grid sample interpolation mode.
Definition: NvInfer.h:5991
bool setSampleMode(SampleMode mode) noexcept
Set the sample mode.
Definition: NvInfer.h:6037
void setAlignCorners(bool alignCorners) noexcept
Set the align corners mode.
Definition: NvInfer.h:6013
apiv::VGridSampleLayer * mImpl
Definition: NvInfer.h:6055
SampleMode getSampleMode() const noexcept
Get the sample mode.
Definition: NvInfer.h:6049
InterpolationMode getInterpolationMode() const noexcept
Get the grid sample interpolation mode.
Definition: NvInfer.h:6003
bool getAlignCorners() const noexcept
Get the align corners mode.
Definition: NvInfer.h:6025
virtual ~IGridSampleLayer() noexcept=default
Class to handle library allocated memory that is accessible to the user.
Definition: NvInferRuntime.h:142
A layer that represents the identity function.
Definition: NvInfer.h:3794
apiv::VIdentityLayer * mImpl
Definition: NvInfer.h:3796
virtual ~IIdentityLayer() noexcept=default
This is a base class for Conditional boundary layers.
Definition: NvInfer.h:4445
IIfConditional * getConditional() const noexcept
Get a pointer to the IIfConditional associated with this boundary layer.
Definition: NvInfer.h:4450
virtual ~IIfConditionalBoundaryLayer() noexcept=default
Helper for constructing conditionally-executed subgraphs.
Definition: NvInfer.h:4527
IIfConditionalInputLayer * addInput(ITensor &input) noexcept
Add an If-conditional input.
Definition: NvInfer.h:4568
char const * getName() const noexcept
Return the name of the conditional.
Definition: NvInfer.h:4593
virtual ~IIfConditional() noexcept=default
IConditionLayer * setCondition(ITensor &condition) noexcept
Set the condition tensor for this If-Conditional construct.
Definition: NvInfer.h:4538
IIfConditionalOutputLayer * addOutput(ITensor &trueSubgraphOutput, ITensor &falseSubgraphOutput) noexcept
Add an If-conditional output.
Definition: NvInfer.h:4556
void setName(char const *name) noexcept
Set the name of the conditional.
Definition: NvInfer.h:4583
This layer represents an output of an IIfConditional.
Definition: NvInfer.h:4483
virtual ~IIfConditionalOutputLayer() noexcept=default
Application-implemented interface for calibration.
Definition: NvInfer.h:8120
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:4758
virtual ~IIteratorLayer() noexcept=default
void setReverse(bool reverse) noexcept
Set iteration order to be reverse.
Definition: NvInfer.h:4785
bool getReverse() const noexcept
Check if the iteration order is reverse.
Definition: NvInfer.h:4795
int32_t getAxis() const noexcept
Get axis being iterated over.
Definition: NvInfer.h:4771
void setAxis(int32_t axis) noexcept
Set axis to iterate over.
Definition: NvInfer.h:4763
A LRN layer in a network definition.
Definition: NvInfer.h:1712
int64_t getWindowSize() const noexcept
Get the LRN window size.
Definition: NvInfer.h:1733
float getAlpha() const noexcept
Get the LRN alpha value.
Definition: NvInfer.h:1755
void setWindowSize(int64_t windowSize) noexcept
Set the LRN window size.
Definition: NvInfer.h:1723
void setK(float k) noexcept
Set the LRN K value.
Definition: NvInfer.h:1789
void setAlpha(float alpha) noexcept
Set the LRN alpha value.
Definition: NvInfer.h:1745
void setBeta(float beta) noexcept
Set the LRN beta value.
Definition: NvInfer.h:1767
virtual ~ILRNLayer() noexcept=default
float getBeta() const noexcept
Get the LRN beta value.
Definition: NvInfer.h:1777
float getK() const noexcept
Get the LRN K value.
Definition: NvInfer.h:1799
Base class for all layer classes in a network definition.
Definition: NvInfer.h:555
bool precisionIsSet() const noexcept
whether the computational precision has been set for this layer
Definition: NvInfer.h:697
void setMetadata(char const *metadata) noexcept
Set the metadata for this layer.
Definition: NvInfer.h:813
void setPrecision(DataType dataType) noexcept
Set the preferred or required computational precision of this layer in a weakly-typed network.
Definition: NvInfer.h:673
void setName(char const *name) noexcept
Set the name of a layer.
Definition: NvInfer.h:576
void resetPrecision() noexcept
reset the computational precision for this layer
Definition: NvInfer.h:707
int32_t getNbInputs() const noexcept
Get the number of inputs of a layer.
Definition: NvInfer.h:594
char const * getMetadata() const noexcept
Get the metadata of the layer.
Definition: NvInfer.h:826
DataType getOutputType(int32_t index) const noexcept
get the output type of this layer
Definition: NvInfer.h:769
DataType getPrecision() const noexcept
get the computational precision of this layer
Definition: NvInfer.h:685
char const * getName() const noexcept
Return the name of a layer.
Definition: NvInfer.h:586
int32_t getNbOutputs() const noexcept
Get the number of outputs of a layer.
Definition: NvInfer.h:615
bool outputTypeIsSet(int32_t index) const noexcept
whether the output type has been set for this layer
Definition: NvInfer.h:783
ITensor * getOutput(int32_t index) const noexcept
Get the layer output corresponding to the given index.
Definition: NvInfer.h:625
void setInput(int32_t index, ITensor &tensor) noexcept
Replace an input of this layer with a specific tensor.
Definition: NvInfer.h:642
void resetOutputType(int32_t index) noexcept
reset the output type for this layer
Definition: NvInfer.h:795
ITensor * getInput(int32_t index) const noexcept
Get the layer input corresponding to the given index.
Definition: NvInfer.h:607
void setOutputType(int32_t index, DataType dataType) noexcept
Set the output type of this layer in a weakly-typed network.
Definition: NvInfer.h:754
LayerType getType() const noexcept
Return the type of a layer.
Definition: NvInfer.h:562
virtual ~ILayer() noexcept=default
Application-implemented logging interface for the builder, refitter and runtime.
Definition: NvInferRuntime.h:1540
This is a base class for Loop boundary layers.
Definition: NvInfer.h:4422
virtual ~ILoopBoundaryLayer() noexcept=default
ILoop * getLoop() const noexcept
Get a pointer to ILoop associated with this boundary layer.
Definition: NvInfer.h:4427
Helper for creating a recurrent subgraph.
Definition: NvInfer.h:4815
void setName(char const *name) noexcept
Set the name of the loop.
Definition: NvInfer.h:4885
ITripLimitLayer * addTripLimit(ITensor &tensor, TripLimit limit) noexcept
Add a trip-count limiter, based on the given tensor.
Definition: NvInfer.h:4844
IIteratorLayer * addIterator(ITensor &tensor, int32_t axis=0, bool reverse=false) noexcept
Return layer that subscripts tensor by loop iteration.
Definition: NvInfer.h:4857
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:4870
virtual ~ILoop() noexcept=default
char const * getName() const noexcept
Return the name of the loop.
Definition: NvInfer.h:4895
IRecurrenceLayer * addRecurrence(ITensor &initialValue) noexcept
Create a recurrence layer for this loop with initialValue as its first input.
Definition: NvInfer.h:4823
An ILoopOutputLayer is the sole way to get output from a loop.
Definition: NvInfer.h:4658
virtual ~ILoopOutputLayer() noexcept=default
int32_t getAxis() const noexcept
Get axis being concatenated over.
Definition: NvInfer.h:4688
LoopOutput getLoopOutput() const noexcept
Get which kind a loop output has.
Definition: NvInfer.h:4663
void setAxis(int32_t axis) noexcept
Set where to insert the contenation axis. Ignored if getLoopOutput() is kLAST_VALUE.
Definition: NvInfer.h:4680
Layer that represents a Matrix Multiplication.
Definition: NvInfer.h:3686
apiv::VMatrixMultiplyLayer * mImpl
Definition: NvInfer.h:3714
virtual ~IMatrixMultiplyLayer() noexcept=default
MatrixOperation getOperation(int32_t index) const noexcept
Get the operation for an input tensor.
Definition: NvInfer.h:3708
void setOperation(int32_t index, MatrixOperation op) noexcept
Set the operation for an input tensor.
Definition: NvInfer.h:3696
A non-maximum suppression layer in a network definition.
Definition: NvInfer.h:6132
virtual ~INMSLayer() noexcept=default
void setTopKBoxLimit(int32_t limit) noexcept
Set the TopK box limit parameter for the layer.
Definition: NvInfer.h:6169
void setBoundingBoxFormat(BoundingBoxFormat fmt) noexcept
Set the bounding box format parameter for the layer.
Definition: NvInfer.h:6143
BoundingBoxFormat getBoundingBoxFormat() const noexcept
Get the bounding box format parameter for the layer.
Definition: NvInfer.h:6155
apiv::VNMSLayer * mImpl
Definition: NvInfer.h:6205
int32_t getTopKBoxLimit() const noexcept
Get the TopK box limit parameter for the layer.
Definition: NvInfer.h:6179
A network definition for input to the builder.
Definition: NvInfer.h:6628
IConcatenationLayer * addConcatenation(ITensor *const *inputs, int32_t nbInputs) noexcept
Add a concatenation layer to the network.
Definition: NvInfer.h:6821
IShuffleLayer * addShuffle(ITensor &input) noexcept
Add a shuffle layer to the network.
Definition: NvInfer.h:6884
INormalizationLayer * addNormalization(ITensor &input, ITensor &scale, ITensor &bias, uint32_t axesMask) noexcept
Add a normalization layer to the network.
Definition: NvInfer.h:7960
void setName(char const *name) noexcept
Sets the name of the network.
Definition: NvInfer.h:7294
bool markDebug(ITensor &tensor) noexcept
Mark a tensor as a debug tensor.
Definition: NvInfer.h:6700
ILRNLayer * addLRN(ITensor &input, int64_t window, float alpha, float beta, float k) noexcept
Add a LRN layer to the network.
Definition: NvInfer.h:6765
ITopKLayer * addTopK(ITensor &input, TopKOperation op, int32_t k, uint32_t reduceAxes) noexcept
Add a TopK layer to the network.
Definition: NvInfer.h:7044
ICumulativeLayer * addCumulative(ITensor &input, ITensor &axis, CumulativeOperation operation, bool exclusive, bool reverse) noexcept
Add a cumulative layer to the network.
Definition: NvInfer.h:7982
IAssertionLayer * addAssertion(ITensor &condition, char const *message) noexcept
Add an assertion layer to the network.
Definition: NvInfer.h:7610
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:7429
ICastLayer * addCast(ITensor &input, DataType toType) noexcept
Add a cast layer.
Definition: NvInfer.h:7184
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:7508
char const * getName() const noexcept
Returns the name associated with the network.
Definition: NvInfer.h:7308
IParametricReLULayer * addParametricReLU(ITensor &input, ITensor &slope) noexcept
Add a parametric ReLU layer to the network.
Definition: NvInfer.h:7407
ITensor * getOutput(int32_t index) const noexcept
Get the output tensor specified by the given index.
Definition: NvInfer.h:6985
ITensor * getInput(int32_t index) const noexcept
Get the input tensor specified by the given index.
Definition: NvInfer.h:6955
IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7777
bool unmarkOutputForShapes(ITensor &tensor) noexcept
Undo markOutputForShapes.
Definition: NvInfer.h:7389
IFillLayer * addFill(Dims const &dimensions, FillOperation op, DataType outputType) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7661
ILoop * addLoop() noexcept
Add a loop to the network.
Definition: NvInfer.h:7539
IDynamicQuantizeLayer * addDynamicQuantize(ITensor &input, int32_t axis, int32_t blockSize, DataType outputType, DataType scaleType) noexcept
Add a dynamic quantization layer to the network.
Definition: NvInfer.h:7865
IActivationLayer * addActivation(ITensor &input, ActivationType type) noexcept
Add an activation layer to the network.
Definition: NvInfer.h:6746
TRT_DEPRECATED IFillLayer * addFill(Dims const &dimensions, FillOperation op) noexcept
Add a fill layer to the network.
Definition: NvInfer.h:7635
ISliceLayer * addSlice(ITensor &input, Dims const &start, Dims const &size, Dims const &stride) noexcept
Add a slice layer to the network.
Definition: NvInfer.h:7270
virtual ~INetworkDefinition() noexcept=default
TRT_DEPRECATED IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7818
virtual IBuilder & getBuilder() const noexcept
Return the builder from which this INetworkDefinition was created.
Definition: NvInfer.h:7993
INMSLayer * addNMS(ITensor &boxes, ITensor &scores, ITensor &maxOutputBoxesPerClass) noexcept
Add a non-maximum suppression layer to the network.
Definition: NvInfer.h:7917
ILayer * getLayer(int32_t index) const noexcept
Get the layer specified by the given index.
Definition: NvInfer.h:6927
bool getFlag(NetworkDefinitionCreationFlag networkDefinitionCreationFlag) const noexcept
Returns true if the network definition creation flag is set.
Definition: NvInfer.h:7360
IIfConditional * addIfConditional() noexcept
Add an if-then-else to the network.
Definition: NvInfer.h:7554
IErrorRecorder * getErrorRecorder() const noexcept
get the ErrorRecorder assigned to this interface.
Definition: NvInfer.h:7735
ISqueezeLayer * addSqueeze(ITensor &input, ITensor &axes) noexcept
Add a squeeze layer to the network.
Definition: NvInfer.h:8050
IReverseSequenceLayer * addReverseSequence(ITensor &input, ITensor &sequenceLens) noexcept
Add a ReverseSequence layer to the network.
Definition: NvInfer.h:7934
int32_t getNbInputs() const noexcept
Get the number of inputs in the network.
Definition: NvInfer.h:6939
NetworkDefinitionCreationFlags getFlags() const noexcept
Get the network definition creation flags for this network definition object. Defaults to 0.
Definition: NvInfer.h:7348
IQuantizeLayer * addQuantize(ITensor &input, ITensor &scale, DataType outputType) noexcept
Add a quantization layer to the network.
Definition: NvInfer.h:7839
IReduceLayer * addReduce(ITensor &input, ReduceOperation operation, uint32_t reduceAxes, bool keepDimensions) noexcept
Add a reduce layer to the network.
Definition: NvInfer.h:7011
IUnaryLayer * addUnary(ITensor &input, UnaryOperation operation) noexcept
Add a unary layer to the network.
Definition: NvInfer.h:6870
IGridSampleLayer * addGridSample(ITensor &input, ITensor &grid) noexcept
Add a GridSample layer to the network.
Definition: NvInfer.h:7899
void removeTensor(ITensor &tensor) noexcept
remove a tensor from the network definition.
Definition: NvInfer.h:7199
bool areWeightsMarkedRefittable(char const *name) const noexcept
Whether the weight has been marked as refittable.
Definition: NvInfer.h:8031
ISelectLayer * addSelect(ITensor &condition, ITensor &thenInput, ITensor &elseInput) noexcept
Add a select layer to the network.
Definition: NvInfer.h:7593
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:7797
int32_t getNbLayers() const noexcept
Get the number of layers in the network.
Definition: NvInfer.h:6913
TRT_DEPRECATED bool hasImplicitBatchDimension() const noexcept
Query whether the network was created with an implicit batch dimension.
Definition: NvInfer.h:7338
apiv::VNetworkDefinition * mImpl
Definition: NvInfer.h:8077
bool markOutputForShapes(ITensor &tensor) noexcept
Enable tensor's value to be computed by IExecutionContext::getShapeBinding.
Definition: NvInfer.h:7377
IOneHotLayer * addOneHot(ITensor &indices, ITensor &values, ITensor &depth, int32_t axis) noexcept
Add a OneHot layer to the network.
Definition: NvInfer.h:6901
IScaleLayer * addScale(ITensor &input, ScaleMode mode, Weights shift, Weights scale, Weights power) noexcept
Add a Scale layer to the network.
Definition: NvInfer.h:6791
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:7250
void unmarkOutput(ITensor &tensor) noexcept
unmark a tensor as a network output.
Definition: NvInfer.h:7211
IIdentityLayer * addIdentity(ITensor &input) noexcept
Add an identity layer.
Definition: NvInfer.h:7169
IGatherLayer * addGatherV2(ITensor &data, ITensor &indices, GatherMode mode) noexcept
Add gather with specified mode, axis=0 and nbElementWiseDims=0.
Definition: NvInfer.h:7076
IElementWiseLayer * addElementWise(ITensor &input1, ITensor &input2, ElementWiseOperation op) noexcept
Add an elementwise layer to the network.
Definition: NvInfer.h:6848
IConstantLayer * addConstant(Dims const &dimensions, Weights weights) noexcept
Add a constant layer to the network.
Definition: NvInfer.h:7155
void setErrorRecorder(IErrorRecorder *recorder) noexcept
Set the ErrorRecorder for this interface.
Definition: NvInfer.h:7720
IPoolingLayer * addPoolingNd(ITensor &input, PoolingType type, Dims const &windowSize) noexcept
Add a multi-dimension pooling layer to the network.
Definition: NvInfer.h:7449
IRaggedSoftMaxLayer * addRaggedSoftMax(ITensor &input, ITensor &bounds) noexcept
Add a RaggedSoftMax layer to the network.
Definition: NvInfer.h:7095
IShapeLayer * addShape(ITensor &input) noexcept
Add a shape layer to the network.
Definition: NvInfer.h:7324
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:7060
bool unmarkWeightsRefittable(char const *name) noexcept
Unmark weights as refittable when the builder flag kREFIT_INDIVIDUAL is set.
Definition: NvInfer.h:8018
bool markWeightsRefittable(char const *name) noexcept
Mark weights as refittable when the builder flag kREFIT_INDIVIDUAL is set.
Definition: NvInfer.h:8006
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:7471
IResizeLayer * addResize(ITensor &input) noexcept
Add a resize layer to the network.
Definition: NvInfer.h:7525
IUnsqueezeLayer * addUnsqueeze(ITensor &input, ITensor &axes) noexcept
Add an unsqueeze layer to the network.
Definition: NvInfer.h:8071
IMatrixMultiplyLayer * addMatrixMultiply(ITensor &input0, MatrixOperation op0, ITensor &input1, MatrixOperation op1) noexcept
Add a MatrixMultiply layer to the network.
Definition: NvInfer.h:7116
ISoftMaxLayer * addSoftMax(ITensor &input) noexcept
Add a SoftMax layer to the network.
Definition: NvInfer.h:6804
bool isDebugTensor(nvinfer1::ITensor const &tensor) const noexcept
Check if a tensor is marked as debug tensor.
Definition: NvInfer.h:6726
bool unmarkDebug(ITensor &tensor) noexcept
Unmark a tensor as a debug tensor.
Definition: NvInfer.h:6716
IEinsumLayer * addEinsum(ITensor *const *inputs, int32_t nbInputs, char const *equation) noexcept
Add an Einsum layer to the network.
Definition: NvInfer.h:7881
void markOutput(ITensor &tensor) noexcept
Mark a tensor as a network output.
Definition: NvInfer.h:6682
TRT_DEPRECATED 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:7232
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:7677
INonZeroLayer * addNonZero(ITensor &input) noexcept
Add a nonzero layer to the network.
Definition: NvInfer.h:7131
TRT_DEPRECATED IDequantizeLayer * addDequantize(ITensor &input, ITensor &scale) noexcept
Add a dequantization layer to the network.
Definition: NvInfer.h:7756
int32_t getNbOutputs() const noexcept
Get the number of outputs in the network.
Definition: NvInfer.h:6969
bool setWeightsName(Weights weights, char const *name) noexcept
Associate a name with all current uses of the given weights.
Definition: NvInfer.h:7701
Forward declaration of IEngineInspector for use by other interfaces.
Definition: NvInferRuntime.h:51
Definition: NvInfer.h:3740
virtual ~INonZeroLayer() noexcept=default
A normalization layer in a network definition.
Definition: NvInfer.h:6294
float getEpsilon() const noexcept
Get the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6313
uint32_t getAxes() const noexcept
Get the axes value used for the normalization calculation.
Definition: NvInfer.h:6333
virtual ~INormalizationLayer() noexcept=default
void setEpsilon(float eps) noexcept
Set the epsilon value used for the normalization calculation.
Definition: NvInfer.h:6303
DataType getComputePrecision() const noexcept
Get the compute precision of this layer.
Definition: NvInfer.h:6400
apiv::VNormalizationLayer * mImpl
Definition: NvInfer.h:6406
int64_t getNbGroups() const noexcept
Get the number of groups used to split the channels for the normalization calculation.
Definition: NvInfer.h:6364
void setAxes(uint32_t axesMask) noexcept
Set the reduction axes for the normalization calculation.
Definition: NvInfer.h:6323
void setComputePrecision(DataType type) noexcept
Set the compute precision of this layer.
Definition: NvInfer.h:6390
void setNbGroups(int64_t nbGroups) noexcept
Set the number of groups used to split the channels in the normalization calculation.
Definition: NvInfer.h:6354
A OneHot layer in a network definition.
Definition: NvInfer.h:5948
apiv::VOneHotLayer * mImpl
Definition: NvInfer.h:5969
void setAxis(int32_t axis) noexcept
Set the axis parameter.
Definition: NvInfer.h:5955
int32_t getAxis() const noexcept
Get the value of the axis parameter.
Definition: NvInfer.h:5963
Optimization profile for dynamic input dimensions and shape tensors.
Definition: NvInferRuntime.h:2616
Layer that represents a padding operation.
Definition: NvInfer.h:2964
Dims getPostPaddingNd() const noexcept
Get the padding that is applied at the end of the tensor.
Definition: NvInfer.h:3013
void setPrePaddingNd(Dims const &padding) noexcept
Set the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2975
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:3001
Dims getPrePaddingNd() const noexcept
Get the padding that is applied at the start of the tensor.
Definition: NvInfer.h:2987
apiv::VPaddingLayer * mImpl
Definition: NvInfer.h:3019
Layer that represents a parametric ReLU operation.
Definition: NvInfer.h:3910
apiv::VParametricReLULayer * mImpl
Definition: NvInfer.h:3912
virtual ~IParametricReLULayer() noexcept=default
Single registration point for all plugins in an application. It is used to find plugin implementation...
Definition: NvInferRuntimeCommon.h:56
Plugin class for user-implemented layers.
Definition: NvInferRuntimePlugin.h:133
Layer type for pluginV2.
Definition: NvInfer.h:2701
virtual ~IPluginV2Layer() noexcept=default
apiv::VPluginV2Layer * mImpl
Definition: NvInfer.h:2714
IPluginV2 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:2708
Layer type for V3 plugins.
Definition: NvInfer.h:2728
virtual ~IPluginV3Layer() noexcept=default
IPluginV3 & getPlugin() noexcept
Get the plugin for the layer.
Definition: NvInfer.h:2735
apiv::VPluginV3Layer * mImpl
Definition: NvInfer.h:2741
A Pooling layer in a network definition.
Definition: NvInfer.h:1461
PoolingType getPoolingType() const noexcept
Get the type of activation to be performed.
Definition: NvInfer.h:1480
PaddingMode getPaddingMode() const noexcept
Get the padding mode.
Definition: NvInfer.h:1613
Dims getPostPadding() const noexcept
Get the padding.
Definition: NvInfer.h:1589
bool getAverageCountExcludesPadding() const noexcept
Get whether average pooling uses as a denominator the overlap area between the window and the unpadde...
Definition: NvInfer.h:1533
Dims getPrePadding() const noexcept
Get the pre-padding.
Definition: NvInfer.h:1561
void setPoolingType(PoolingType type) noexcept
Set the type of activation to be performed.
Definition: NvInfer.h:1470
void setWindowSizeNd(Dims const &windowSize) noexcept
Set the multi-dimension window size for pooling.
Definition: NvInfer.h:1626
void setPaddingMode(PaddingMode paddingMode) noexcept
Set the padding mode.
Definition: NvInfer.h:1602
Dims getWindowSizeNd() const noexcept
Get the multi-dimension window size for pooling.
Definition: NvInfer.h:1636
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:1522
void setPaddingNd(Dims const &padding) noexcept
Set the multi-dimension padding for pooling.
Definition: NvInfer.h:1680
float getBlendFactor() const noexcept
Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1508
void setStrideNd(Dims const &stride) noexcept
Set the multi-dimension stride for pooling.
Definition: NvInfer.h:1651
Dims getStrideNd() const noexcept
Get the multi-dimension stride for pooling.
Definition: NvInfer.h:1661
virtual ~IPoolingLayer() noexcept=default
Dims getPaddingNd() const noexcept
Get the multi-dimension padding for pooling.
Definition: NvInfer.h:1692
void setPostPadding(Dims const &padding) noexcept
Set the multi-dimension post-padding for pooling.
Definition: NvInfer.h:1579
void setPrePadding(Dims const &padding) noexcept
Set the multi-dimension pre-padding for pooling.
Definition: NvInfer.h:1551
void setBlendFactor(float blendFactor) noexcept
Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPo...
Definition: NvInfer.h:1495
A Quantize layer in a network definition.
Definition: NvInfer.h:5397
void setToType(DataType toType) noexcept
Set the Quantize layer output type.
Definition: NvInfer.h:5434
void setAxis(int32_t axis) noexcept
Set the quantization axis.
Definition: NvInfer.h:5418
int32_t getAxis() const noexcept
Get the quantization axis.
Definition: NvInfer.h:5407
virtual ~IQuantizeLayer() noexcept=default
DataType getToType() const noexcept
Return the Quantize layer output type.
Definition: NvInfer.h:5446
A RaggedSoftmax layer in a network definition.
Definition: NvInfer.h:3761
apiv::VRaggedSoftMaxLayer * mImpl
Definition: NvInfer.h:3763
virtual ~IRaggedSoftMaxLayer() noexcept=default
A recurrence layer in a network definition.
Definition: NvInfer.h:4611
virtual ~IRecurrenceLayer() noexcept=default
Layer that represents a reduction across a non-bool tensor.
Definition: NvInfer.h:2884
void setKeepDimensions(bool keepDimensions) noexcept
Set the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2931
void setOperation(ReduceOperation op) noexcept
Set the reduce operation for the layer.
Definition: NvInfer.h:2891
ReduceOperation getOperation() const noexcept
Get the reduce operation for the layer.
Definition: NvInfer.h:2901
virtual ~IReduceLayer() noexcept=default
uint32_t getReduceAxes() const noexcept
Get the axes over which to reduce for the layer.
Definition: NvInfer.h:2921
void setReduceAxes(uint32_t reduceAxes) noexcept
Set the axes over which to reduce.
Definition: NvInfer.h:2911
apiv::VReduceLayer * mImpl
Definition: NvInfer.h:2947
bool getKeepDimensions() const noexcept
Get the boolean that specifies whether or not to keep the reduced dimensions for the layer.
Definition: NvInfer.h:2941
A resize layer in a network definition.
Definition: NvInfer.h:4099
void setSelectorForSinglePixel(ResizeSelector selector) noexcept
Set coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4260
void setNearestRounding(ResizeRoundMode value) noexcept
Set rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4284
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:4178
void setOutputDimensions(Dims const &dimensions) noexcept
Set the output dimensions.
Definition: NvInfer.h:4119
void setCubicCoeff(float A) noexcept
Set the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4316
void setScales(float const *scales, int32_t nbScales) noexcept
Set the resize scales.
Definition: NvInfer.h:4159
float getCubicCoeff() const noexcept
Get the coefficient 'A' used in cubic interpolation.
Definition: NvInfer.h:4326
ResizeSelector getSelectorForSinglePixel() const noexcept
Get the coordinate selector function when resized to single pixel.
Definition: NvInfer.h:4270
InterpolationMode getResizeMode() const noexcept
Get resize mode for an input tensor.
Definition: NvInfer.h:4200
void setCoordinateTransformation(ResizeCoordinateTransformation coordTransform) noexcept
Set coordinate transformation function.
Definition: NvInfer.h:4235
void setExcludeOutside(bool excludeFlag) noexcept
Set the state for excluding outside pixels.
Definition: NvInfer.h:4339
void setResizeMode(InterpolationMode interpolationMode) noexcept
Set resize mode for an input tensor.
Definition: NvInfer.h:4190
Dims getOutputDimensions() const noexcept
Get the output dimensions.
Definition: NvInfer.h:4129
ResizeRoundMode getNearestRounding() const noexcept
Get rounding mode for nearest neighbor resize.
Definition: NvInfer.h:4294
bool getExcludeOutside() const noexcept
Get the state for excluding outside pixels.
Definition: NvInfer.h:4349
ResizeCoordinateTransformation getCoordinateTransformation() const noexcept
Get coordinate transformation function.
Definition: NvInfer.h:4245
A ReverseSequence layer in a network definition.
Definition: NvInfer.h:6222
void setSequenceAxis(int32_t sequenceAxis) noexcept
Set the sequence axis. Default is 0.
Definition: NvInfer.h:6255
int32_t getBatchAxis() const noexcept
Return the batch axis. Return 1 if no batch axis was set.
Definition: NvInfer.h:6242
apiv::VReverseSequenceLayer * mImpl
Definition: NvInfer.h:6271
int32_t getSequenceAxis() const noexcept
Return the sequence axis. Return 0 if no sequence axis was set.
Definition: NvInfer.h:6265
void setBatchAxis(int32_t batchAxis) noexcept
Set the batch axis. Default is 1.
Definition: NvInfer.h:6232
virtual ~IReverseSequenceLayer() noexcept=default
A Scale layer in a network definition.
Definition: NvInfer.h:1858
Weights getScale() const noexcept
Get the scale value.
Definition: NvInfer.h:1915
Weights getPower() const noexcept
Get the power value.
Definition: NvInfer.h:1935
void setScale(Weights scale) noexcept
Set the scale value.
Definition: NvInfer.h:1905
void setPower(Weights power) noexcept
Set the power value.
Definition: NvInfer.h:1925
ScaleMode getMode() const noexcept
Get the scale mode.
Definition: NvInfer.h:1875
void setShift(Weights shift) noexcept
Set the shift value.
Definition: NvInfer.h:1885
void setChannelAxis(int32_t channelAxis) noexcept
Set the channel axis.
Definition: NvInfer.h:1971
Weights getShift() const noexcept
Get the shift value.
Definition: NvInfer.h:1895
virtual ~IScaleLayer() noexcept=default
void setMode(ScaleMode mode) noexcept
Set the scale mode.
Definition: NvInfer.h:1865
int32_t getChannelAxis() const noexcept
Get the channel axis.
Definition: NvInfer.h:1950
A scatter layer in a network definition. Supports several kinds of scattering.
Definition: NvInfer.h:5876
void setMode(ScatterMode mode) noexcept
Set the scatter mode.
Definition: NvInfer.h:5883
apiv::VScatterLayer * mImpl
Definition: NvInfer.h:5917
void setAxis(int32_t axis) noexcept
Set the axis used by ScatterMode::kELEMENTS.
Definition: NvInfer.h:5903
int32_t getAxis() const noexcept
Get the axis.
Definition: NvInfer.h:5911
ScatterMode getMode() const noexcept
Get the scatter mode.
Definition: NvInfer.h:5893
virtual ~IScatterLayer() noexcept=default
Select elements from two data tensors based on a condition tensor.
Definition: NvInfer.h:4918
virtual ~ISelectLayer() noexcept=default
Layer type for getting shape of a tensor.
Definition: NvInfer.h:3489
virtual ~IShapeLayer() noexcept=default
apiv::VShapeLayer * mImpl
Definition: NvInfer.h:3491
Layer type for shuffling data.
Definition: NvInfer.h:3052
apiv::VShuffleLayer * mImpl
Definition: NvInfer.h:3210
void setFirstTranspose(Permutation permutation) noexcept
Set the permutation applied by the first transpose operation.
Definition: NvInfer.h:3063
void setSecondTranspose(Permutation permutation) noexcept
Set the permutation applied by the second transpose operation.
Definition: NvInfer.h:3163
Dims getReshapeDimensions() const noexcept
Get the reshaped dimensions.
Definition: NvInfer.h:3116
void setReshapeDimensions(Dims const &dimensions) noexcept
Set the reshaped dimensions.
Definition: NvInfer.h:3103
Permutation getFirstTranspose() const noexcept
Get the permutation applied by the first transpose operation.
Definition: NvInfer.h:3075
virtual ~IShuffleLayer() noexcept=default
Permutation getSecondTranspose() const noexcept
Get the permutation applied by the second transpose operation.
Definition: NvInfer.h:3175
bool getZeroIsPlaceholder() const noexcept
Get meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3204
void setZeroIsPlaceholder(bool zeroIsPlaceholder) noexcept
Set meaning of 0 in reshape dimensions.
Definition: NvInfer.h:3191
Slices an input tensor into an output tensor based on the offset and strides.
Definition: NvInfer.h:3304
void setStride(Dims const &stride) noexcept
Set the stride for computing the output slice data.
Definition: NvInfer.h:3373
apiv::VSliceLayer * mImpl
Definition: NvInfer.h:3472
virtual ~ISliceLayer() noexcept=default
void setSize(Dims const &size) noexcept
Set the dimensions of the output slice.
Definition: NvInfer.h:3344
void setAxes(Dims const &axes) noexcept
Set the axes for this ISliceLayer.
Definition: NvInfer.h:3451
void setStart(Dims const &start) noexcept
Set the start offset that the slice layer uses to create the output slice.
Definition: NvInfer.h:3315
Dims getStart() const noexcept
Get the start offset for the slice layer.
Definition: NvInfer.h:3330
void setMode(SampleMode mode) noexcept
Set the slice mode.
Definition: NvInfer.h:3398
Dims getSize() const noexcept
Get dimensions of the output slice.
Definition: NvInfer.h:3359
SampleMode getMode() const noexcept
Get the slice mode.
Definition: NvInfer.h:3408
Dims getStride() const noexcept
Get the stride for the output slice.
Definition: NvInfer.h:3388
Dims getAxes() const noexcept
Get the axes for this ISliceLayer.
Definition: NvInfer.h:3466
A Softmax layer in a network definition.
Definition: NvInfer.h:2002
void setAxes(uint32_t axes) noexcept
Set the axis along which softmax is computed. Currently, only one axis can be set.
Definition: NvInfer.h:2024
uint32_t getAxes() const noexcept
Get the axis along which softmax occurs.
Definition: NvInfer.h:2034
virtual ~ISoftMaxLayer() noexcept=default
Layer that represents a squeeze operation, removing unit dimensions of the input tensor on a set of a...
Definition: NvInfer.h:6419
virtual ~ISqueezeLayer() noexcept=default
apiv::VSqueezeLayer * mImpl
Definition: NvInfer.h:6436
A tensor in a network definition.
Definition: NvInfer.h:185
void setAllowedFormats(TensorFormats formats) noexcept
Set allowed formats for an input or output tensor. By default all formats are allowed....
Definition: NvInfer.h:431
TensorLocation getLocation() const noexcept
Get the storage location of a tensor.
Definition: NvInfer.h:350
void setDimensions(Dims const &dimensions) noexcept
Set the dimensions of a tensor.
Definition: NvInfer.h:233
void resetDynamicRange() noexcept
Undo effect of setDynamicRange.
Definition: NvInfer.h:389
void setName(char const *name) noexcept
Set the tensor name.
Definition: NvInfer.h:202
bool isExecutionTensor() const noexcept
Whether the tensor is an execution tensor.
Definition: NvInfer.h:496
void setType(DataType type) noexcept
Set the data type of a tensor.
Definition: NvInfer.h:262
TRT_DEPRECATED bool dynamicRangeIsSet() const noexcept
Query whether dynamic range is set.
Definition: NvInfer.h:381
char const * getName() const noexcept
Get the tensor name.
Definition: NvInfer.h:214
bool isShapeTensor() const noexcept
Whether the tensor is a shape tensor.
Definition: NvInfer.h:475
float getDynamicRangeMax() const noexcept
Get maximum of dynamic range.
Definition: NvInfer.h:409
bool isNetworkInput() const noexcept
Whether the tensor is a network input.
Definition: NvInfer.h:299
TRT_DEPRECATED void setBroadcastAcrossBatch(bool broadcastAcrossBatch) noexcept
Set whether to enable broadcast of tensor across the implicit batch dimension.
Definition: NvInfer.h:324
TRT_DEPRECATED bool setDynamicRange(float min, float max) noexcept
Set dynamic range for the tensor.
Definition: NvInfer.h:291
TRT_DEPRECATED bool getBroadcastAcrossBatch() const noexcept
Check if tensor is broadcast across the implicit batch dimension.
Definition: NvInfer.h:338
bool isNetworkOutput() const noexcept
Whether the tensor is a network output.
Definition: NvInfer.h:307
DataType getType() const noexcept
Get the data type of a tensor.
Definition: NvInfer.h:274
apiv::VTensor * mImpl
Definition: NvInfer.h:543
float getDynamicRangeMin() const noexcept
Get minimum of dynamic range.
Definition: NvInfer.h:399
virtual ~ITensor() noexcept=default
void setDimensionName(int32_t index, char const *name) noexcept
Name a dimension of an input tensor.
Definition: NvInfer.h:522
char const * getDimensionName(int32_t index) const noexcept
Get the name of an input dimension.
Definition: NvInfer.h:537
TRT_DEPRECATED void setLocation(TensorLocation location) noexcept
Set the storage location of a tensor.
Definition: NvInfer.h:369
Dims getDimensions() const noexcept
Get the dimensions of a tensor.
Definition: NvInfer.h:247
TensorFormats getAllowedFormats() const noexcept
Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor,...
Definition: NvInfer.h:444
Class to handle tactic timing info collected from builder.
Definition: NvInfer.h:8967
int64_t queryKeys(TimingCacheKey *keyBuffer, int64_t capacity) const noexcept
Query cache keys from Timing Cache.
Definition: NvInfer.h:9033
bool combine(ITimingCache const &inputCache, bool ignoreMismatch) noexcept
Combine input timing cache into local instance.
Definition: NvInfer.h:9004
TimingCacheValue query(TimingCacheKey const &key) const noexcept
Query value in a cache entry.
Definition: NvInfer.h:9050
virtual ~ITimingCache() noexcept=default
bool update(TimingCacheKey const &key, TimingCacheValue const &value) noexcept
Update values in a cache entry.
Definition: NvInfer.h:9072
apiv::VTimingCache * mImpl
Definition: NvInfer.h:9078
bool reset() noexcept
Empty the timing cache.
Definition: NvInfer.h:9014
Layer that represents a TopK reduction.
Definition: NvInfer.h:3529
void setK(int32_t k) noexcept
Set the static k value for the layer.
Definition: NvInfer.h:3560
void setReduceAxes(uint32_t reduceAxes) noexcept
Set which axes to reduce for the layer.
Definition: NvInfer.h:3584
TopKOperation getOperation() const noexcept
Get the operation for the layer.
Definition: NvInfer.h:3546
apiv::VTopKLayer * mImpl
Definition: NvInfer.h:3616
void setOperation(TopKOperation op) noexcept
Set the operation for the layer.
Definition: NvInfer.h:3536
int32_t getK() const noexcept
Get the k value for the layer.
Definition: NvInfer.h:3574
uint32_t getReduceAxes() const noexcept
Get the axes to reduce for the layer.
Definition: NvInfer.h:3594
virtual ~ITopKLayer() noexcept=default
A layer that represents a trip-count limiter.
Definition: NvInfer.h:4732
TripLimit getTripLimit() const noexcept
Get a trip limiter type.
Definition: NvInfer.h:4737
virtual ~ITripLimitLayer() noexcept=default
Layer that represents an unary operation.
Definition: NvInfer.h:2809
void setOperation(UnaryOperation op) noexcept
Set the unary operation for the layer.
Definition: NvInfer.h:2818
apiv::VUnaryLayer * mImpl
Definition: NvInfer.h:2834
UnaryOperation getOperation() const noexcept
Get the unary operation for the layer.
Definition: NvInfer.h:2828
virtual ~IUnaryLayer() noexcept=default
Layer that represents an unsqueeze operation, which reshapes the input tensor by inserting unit-lengt...
Definition: NvInfer.h:6448
virtual ~IUnsqueezeLayer() noexcept=default
apiv::VUnsqueezeLayer * mImpl
Definition: NvInfer.h:6465
An Interface class for version control.
Definition: NvInferRuntimeBase.h:263
Version information associated with a TRT interface.
Definition: NvInferRuntimeBase.h:228
An array of weights used as a layer parameter.
Definition: NvInferRuntime.h:124
Definition: NvInfer.h:8599
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:8604
virtual ~IAlgorithmSelector() noexcept=default
Definition: NvInferRuntimeBase.h:400
Definition: NvInferRuntime.h:1608
Definition: NvInfer.h:8226
~IInt8EntropyCalibrator2() noexcept override=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8239
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:8231
Definition: NvInfer.h:8186
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8199
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:8191
~IInt8EntropyCalibrator() noexcept override=default
Definition: NvInfer.h:8305
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8318
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:8310
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:8266
~IInt8MinMaxCalibrator() noexcept override=default
CalibrationAlgoType getAlgorithm() noexcept override
Definition: NvInfer.h:8279
InterfaceInfo getInterfaceInfo() const noexcept override
Return version information associated with this interface. Applications must not override this method...
Definition: NvInfer.h:8271
Definition: NvInferPluginBase.h:206
Definition: NvInfer.h:9276
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:10627
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:2832
ResizeSelector
The coordinate selector when resize to single pixel output.
Definition: NvInfer.h:4004
@ kFORMULA
Use formula to map the original index.
@ kUPPER
Select the upper left pixel.