Tensorrt7 support dynamic input.
//!
//! \brief Builds an engine for preprocessing (mPreprocessorEngine).
//!
void SampleDynamicReshape::buildPreprocessorEngine(const SampleUniquePtr<nvinfer1::IBuilder>& builder)
{
// Create the preprocessor engine using a network that supports full dimensions (createNetworkV2).
auto preprocessorNetwork = makeUnique(
builder->createNetworkV2(1U << static_cast<uint32_t>(NetworkDefinitionCreationFlag::kEXPLICIT_BATCH)));
// Reshape a dynamically shaped input to the size expected by the model, (1, 1, 28, 28).
auto input = preprocessorNetwork->addInput("input", nvinfer1::DataType::kFLOAT, Dims4{1, 1, -1, -1});
auto resizeLayer = preprocessorNetwork->addResize(*input);
resizeLayer->setOutputDimensions(mPredictionInputDims);
preprocessorNetwork->markOutput(*resizeLayer->getOutput(0));
// Finally, configure and build the preprocessor engine.
auto preprocessorConfig = makeUnique(builder->createBuilderConfig());
// Create an optimization profile so that we can specify a range of input dimensions.
auto profile = builder->createOptimizationProfile();
In this sample, if I addInput with some dimensions with -1, createNetworkV2 with kEXPLICIT_BATCH is required？And create an optimization profile is required？