TensorRT
8.0.3
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Go to the source code of this file.
Classes | |
struct | nvinfer1::impl::EnumMaxImpl< ActivationType > |
Maximum number of elements in ActivationType enum. More... | |
class | nvinfer1::ITensor |
A tensor in a network definition. More... | |
class | nvinfer1::ILayer |
Base class for all layer classes in a network definition. More... | |
struct | nvinfer1::impl::EnumMaxImpl< PaddingMode > |
Maximum number of elements in PaddingMode enum. More... | |
class | nvinfer1::IConvolutionLayer |
A convolution layer in a network definition. More... | |
class | nvinfer1::IFullyConnectedLayer |
A fully connected layer in a network definition. This layer expects an input tensor of three or more non-batch dimensions. The input is automatically reshaped into an MxV tensor X , where V is a product of the last three dimensions and M is a product of the remaining dimensions (where the product over 0 dimensions is defined as 1). For example: More... | |
class | nvinfer1::IActivationLayer |
An Activation layer in a network definition. More... | |
struct | nvinfer1::impl::EnumMaxImpl< PoolingType > |
Maximum number of elements in PoolingType enum. More... | |
class | nvinfer1::IPoolingLayer |
A Pooling layer in a network definition. More... | |
class | nvinfer1::ILRNLayer |
A LRN layer in a network definition. More... | |
class | nvinfer1::IScaleLayer |
A Scale layer in a network definition. More... | |
class | nvinfer1::ISoftMaxLayer |
A Softmax layer in a network definition. More... | |
class | nvinfer1::IConcatenationLayer |
A concatenation layer in a network definition. More... | |
class | nvinfer1::IDeconvolutionLayer |
A deconvolution layer in a network definition. More... | |
struct | nvinfer1::impl::EnumMaxImpl< ElementWiseOperation > |
Maximum number of elements in ElementWiseOperation enum. More... | |
class | nvinfer1::IElementWiseLayer |
A elementwise layer in a network definition. More... | |
class | nvinfer1::IGatherLayer |
class | nvinfer1::IRNNv2Layer |
An RNN layer in a network definition, version 2. More... | |
class | nvinfer1::IPluginV2Layer |
Layer type for pluginV2. More... | |
class | nvinfer1::IUnaryLayer |
Layer that represents an unary operation. More... | |
class | nvinfer1::IReduceLayer |
Layer that represents a reduction operator across Shape, Int32, Float, and Half tensors. More... | |
class | nvinfer1::IPaddingLayer |
Layer that represents a padding operation. More... | |
struct | nvinfer1::Permutation |
class | nvinfer1::IShuffleLayer |
Layer type for shuffling data. More... | |
class | nvinfer1::ISliceLayer |
Slices an input tensor into an output tensor based on the offset and strides. More... | |
class | nvinfer1::IShapeLayer |
Layer type for getting shape of a tensor. More... | |
class | nvinfer1::ITopKLayer |
Layer that represents a TopK reduction. More... | |
class | nvinfer1::IMatrixMultiplyLayer |
Layer that represents a Matrix Multiplication. More... | |
class | nvinfer1::IRaggedSoftMaxLayer |
A RaggedSoftmax layer in a network definition. More... | |
class | nvinfer1::IIdentityLayer |
A layer that represents the identity function. More... | |
class | nvinfer1::IConstantLayer |
Layer that represents a constant value. More... | |
class | nvinfer1::IParametricReLULayer |
Layer that represents a parametric ReLU operation. More... | |
struct | nvinfer1::impl::EnumMaxImpl< ResizeMode > |
Maximum number of elements in ResizeMode enum. More... | |
struct | nvinfer1::impl::EnumMaxImpl< ResizeCoordinateTransformation > |
Maximum number of elements in ResizeCoordinateTransformation enum. More... | |
struct | nvinfer1::impl::EnumMaxImpl< ResizeSelector > |
Maximum number of elements in ResizeSelector enum. More... | |
struct | nvinfer1::impl::EnumMaxImpl< ResizeRoundMode > |
Maximum number of elements in ResizeRoundMode enum. More... | |
class | nvinfer1::IResizeLayer |
A resize layer in a network definition. More... | |
class | nvinfer1::ILoopBoundaryLayer |
class | nvinfer1::IRecurrenceLayer |
class | nvinfer1::ILoopOutputLayer |
class | nvinfer1::ITripLimitLayer |
class | nvinfer1::IIteratorLayer |
class | nvinfer1::ILoop |
class | nvinfer1::ISelectLayer |
class | nvinfer1::IFillLayer |
Generate an output tensor with specified mode. More... | |
class | nvinfer1::IQuantizeLayer |
A Quantize layer in a network definition. More... | |
class | nvinfer1::IDequantizeLayer |
A Dequantize layer in a network definition. More... | |
class | nvinfer1::INetworkDefinition |
A network definition for input to the builder. More... | |
class | nvinfer1::IInt8Calibrator |
Application-implemented interface for calibration. More... | |
class | nvinfer1::IInt8EntropyCalibrator |
class | nvinfer1::IInt8EntropyCalibrator2 |
class | nvinfer1::IInt8MinMaxCalibrator |
class | nvinfer1::IInt8LegacyCalibrator |
class | nvinfer1::IAlgorithmIOInfo |
Carries information about input or output of the algorithm. IAlgorithmIOInfo for all the input and output along with IAlgorithmVariant denotes the variation of algorithm and can be used to select or reproduce an algorithm using IAlgorithmSelector::selectAlgorithms(). More... | |
class | nvinfer1::IAlgorithmVariant |
provides a unique 128-bit identifier, which along with the input and output information denotes the variation of algorithm and can be used to select or reproduce an algorithm, using IAlgorithmSelector::selectAlgorithms() More... | |
class | nvinfer1::IAlgorithmContext |
Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorithm. More... | |
class | nvinfer1::IAlgorithm |
Describes a variation of execution of a layer. An algorithm is represented by IAlgorithmVariant and the IAlgorithmIOInfo for each of its inputs and outputs. An algorithm can be selected or reproduced using AlgorithmSelector::selectAlgorithms().". More... | |
class | nvinfer1::IAlgorithmSelector |
Interface implemented by application for selecting and reporting algorithms of a layer provided by the builder. More... | |
class | nvinfer1::ITimingCache |
Class to handle tactic timing info collected from builder. More... | |
class | nvinfer1::IBuilderConfig |
Holds properties for configuring a builder to produce an engine. More... | |
class | nvinfer1::IBuilder |
Builds an engine from a network definition. More... | |
Namespaces | |
nvinfer1 | |
The TensorRT API version 1 namespace. | |
Typedefs | |
using | nvinfer1::TensorFormats = uint32_t |
It is capable of representing one or more TensorFormat by binary OR operations, e.g., 1U << TensorFormat::kCHW4 | 1U << TensorFormat::kCHW32. More... | |
using | nvinfer1::QuantizationFlags = uint32_t |
Represents one or more QuantizationFlag values using binary OR operations. More... | |
using | nvinfer1::BuilderFlags = uint32_t |
Represents one or more QuantizationFlag values using binary OR operations, e.g., 1U << BuilderFlag::kFP16 | 1U << BuilderFlag::kDEBUG. More... | |
using | nvinfer1::NetworkDefinitionCreationFlags = uint32_t |
Represents one or more NetworkDefinitionCreationFlag flags using binary OR operations. e.g., 1U << NetworkDefinitionCreationFlag::kEXPLICIT_BATCH. More... | |
Functions | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< LayerType > () noexcept |
Maximum number of elements in LayerType enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< ScaleMode > () noexcept |
Maximum number of elements in ScaleMode enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< RNNOperation > () noexcept |
Maximum number of elements in RNNOperation enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< RNNDirection > () noexcept |
Maximum number of elements in RNNDirection enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< RNNInputMode > () noexcept |
Maximum number of elements in RNNInputMode enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< RNNGateType > () noexcept |
Maximum number of elements in RNNGateType enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< UnaryOperation > () noexcept |
Maximum number of elements in UnaryOperation enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< ReduceOperation > () noexcept |
Maximum number of elements in ReduceOperation enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< SliceMode > () noexcept |
Maximum number of elements in SliceMode enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< TopKOperation > () noexcept |
Maximum number of elements in TopKOperation enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< MatrixOperation > () noexcept |
Maximum number of elements in MatrixOperation enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< LoopOutput > () noexcept |
Maximum number of elements in LoopOutput enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< TripLimit > () noexcept |
Maximum number of elements in TripLimit enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< FillOperation > () noexcept |
Maximum number of elements in FillOperation enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< CalibrationAlgoType > () noexcept |
Maximum number of elements in CalibrationAlgoType enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< QuantizationFlag > () noexcept |
Maximum number of quantization flags in QuantizationFlag enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< BuilderFlag > () noexcept |
Maximum number of builder flags in BuilderFlag enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< ProfilingVerbosity > () noexcept |
Maximum number of profile verbosity levels in ProfilingVerbosity enum. More... | |
template<> | |
constexpr int32_t | nvinfer1::EnumMax< NetworkDefinitionCreationFlag > () noexcept |
Maximum number of elements in NetworkDefinitionCreationFlag enum. More... | |
IBuilder * | nvinfer1::anonymous_namespace{NvInfer.h}::createInferBuilder (ILogger &logger) noexcept |
Create an instance of an IBuilder class. More... | |
TensorRT Versioning follows Semantic Versioning Guidelines specified here: https://semver.org/
This is the top-level API file for TensorRT.
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