|
| class | CUDADriverWrapper |
| |
| class | Dims |
| | Structure to define the dimensions of a tensor. More...
|
| |
| class | Dims2 |
| | Descriptor for two-dimensional data. More...
|
| |
| class | Dims3 |
| | Descriptor for three-dimensional data. More...
|
| |
| class | Dims4 |
| | Descriptor for four-dimensional data. More...
|
| |
| class | DimsExprs |
| |
| class | DimsHW |
| | Descriptor for two-dimensional spatial data. More...
|
| |
| class | DynamicPluginTensorDesc |
| |
| class | IActivationLayer |
| | An Activation layer in a network definition. More...
|
| |
| class | 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 | IAlgorithmContext |
| | Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorithm. More...
|
| |
| class | 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 | IAlgorithmSelector |
| | Interface implemented by application for selecting and reporting algorithms of a layer provided by the builder. More...
|
| |
| class | 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 | IBuilder |
| | Builds an engine from a network definition. More...
|
| |
| class | IBuilderConfig |
| | Holds properties for configuring a builder to produce an engine. More...
|
| |
| class | IConcatenationLayer |
| | A concatenation layer in a network definition. More...
|
| |
| class | IConstantLayer |
| | Layer that represents a constant value. More...
|
| |
| class | IConvolutionLayer |
| | A convolution layer in a network definition. More...
|
| |
| class | ICudaEngine |
| | An engine for executing inference on a built network, with functionally unsafe features. More...
|
| |
| class | IDeconvolutionLayer |
| | A deconvolution layer in a network definition. More...
|
| |
| class | IDimensionExpr |
| |
| class | IElementWiseLayer |
| | A elementwise layer in a network definition. More...
|
| |
| class | IErrorRecorder |
| | Reference counted application-implemented error reporting interface for TensorRT objects. More...
|
| |
| class | IExecutionContext |
| | Context for executing inference using an engine, with functionally unsafe features. More...
|
| |
| class | IExprBuilder |
| |
| class | IFillLayer |
| | Generate an output tensor with specified mode. More...
|
| |
| class | 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 | IGatherLayer |
| |
| class | IGpuAllocator |
| | Application-implemented class for controlling allocation on the GPU. More...
|
| |
| class | IHostMemory |
| | Class to handle library allocated memory that is accessible to the user. More...
|
| |
| class | IIdentityLayer |
| | A layer that represents the identity function. More...
|
| |
| class | IInt8Calibrator |
| | Application-implemented interface for calibration. More...
|
| |
| class | IInt8EntropyCalibrator |
| | Entropy calibrator. More...
|
| |
| class | IInt8EntropyCalibrator2 |
| | Entropy calibrator 2. More...
|
| |
| class | IInt8LegacyCalibrator |
| | Legacy calibrator left for backward compatibility with TensorRT 2.0. More...
|
| |
| class | IInt8MinMaxCalibrator |
| | MinMax Calibrator. More...
|
| |
| class | IIteratorLayer |
| |
| class | ILayer |
| | Base class for all layer classes in a network definition. More...
|
| |
| class | ILogger |
| | Application-implemented logging interface for the builder, engine and runtime. More...
|
| |
| class | ILoop |
| | Helper for creating a recurrent subgraph. More...
|
| |
| class | ILoopBoundaryLayer |
| |
| class | ILoopOutputLayer |
| | An ILoopOutputLayer is the sole way to get output from a loop. More...
|
| |
| class | ILRNLayer |
| | A LRN layer in a network definition. More...
|
| |
| class | IMatrixMultiplyLayer |
| | Layer that represents a Matrix Multiplication. More...
|
| |
| class | INetworkDefinition |
| | A network definition for input to the builder. More...
|
| |
| class | IOptimizationProfile |
| | Optimization profile for dynamic input dimensions and shape tensors. More...
|
| |
| class | IPaddingLayer |
| | Layer that represents a padding operation. More...
|
| |
| class | IParametricReLULayer |
| | Layer that represents a parametric ReLU operation. More...
|
| |
| class | IPlugin |
| | Plugin class for user-implemented layers. More...
|
| |
| class | IPluginCreator |
| | Plugin creator class for user implemented layers. More...
|
| |
| class | IPluginExt |
| | Plugin class for user-implemented layers. More...
|
| |
| class | IPluginFactory |
| | Plugin factory for deserialization. More...
|
| |
| class | IPluginRegistry |
| | Single registration point for all plugins in an application. It is used to find plugin implementations during engine deserialization. Internally, the plugin registry is considered to be a singleton so all plugins in an application are part of the same global registry. Note that the plugin registry is only supported for plugins of type IPluginV2 and should also have a corresponding IPluginCreator implementation. More...
|
| |
| class | IPluginV2 |
| | Plugin class for user-implemented layers. More...
|
| |
| class | IPluginV2DynamicExt |
| |
| class | IPluginV2Ext |
| | Plugin class for user-implemented layers. More...
|
| |
| class | IPluginV2IOExt |
| | Plugin class for user-implemented layers. More...
|
| |
| class | IPluginV2Layer |
| | Layer type for pluginV2. More...
|
| |
| class | IPoolingLayer |
| | A Pooling layer in a network definition. More...
|
| |
| class | IProfiler |
| | Application-implemented interface for profiling. More...
|
| |
| class | IRaggedSoftMaxLayer |
| | A RaggedSoftmax layer in a network definition. More...
|
| |
| class | IRecurrenceLayer |
| |
| class | IReduceLayer |
| | Layer that represents a reduction operator across Shape, Int32, Float, and Half tensors. More...
|
| |
| class | IRefitter |
| | Updates weights in an engine. More...
|
| |
| class | IResizeLayer |
| | A resize layer in a network definition. More...
|
| |
| class | IRuntime |
| | Allows a serialized functionally unsafe engine to be deserialized. More...
|
| |
| class | IScaleLayer |
| | A Scale layer in a network definition. More...
|
| |
| class | ISelectLayer |
| |
| class | IShapeLayer |
| | Layer type for getting shape of a tensor. More...
|
| |
| class | IShuffleLayer |
| | Layer type for shuffling data. More...
|
| |
| class | ISliceLayer |
| | Slices an input tensor into an output tensor based on the offset and strides. More...
|
| |
| class | ISoftMaxLayer |
| | A Softmax layer in a network definition. More...
|
| |
| class | ITensor |
| | A tensor in a network definition. More...
|
| |
| class | ITopKLayer |
| | Layer that represents a TopK reduction. More...
|
| |
| class | ITripLimitLayer |
| |
| class | IUnaryLayer |
| | Layer that represents an unary operation. More...
|
| |
| struct | Permutation |
| |
| class | PluginField |
| | Structure containing plugin attribute field names and associated data This information can be parsed to decode necessary plugin metadata. More...
|
| |
| struct | PluginFieldCollection |
| |
| class | PluginRegistrar |
| | Register the plugin creator to the registry The static registry object will be instantiated when the plugin library is loaded. More...
|
| |
| struct | PluginTensorDesc |
| | Fields that a plugin might see for an input or output. More...
|
| |
| class | Weights |
| | An array of weights used as a layer parameter. More...
|
| |
|
| enum | LayerType : int32_t {
LayerType::kCONVOLUTION = 0,
LayerType::kFULLY_CONNECTED = 1,
LayerType::kACTIVATION = 2,
LayerType::kPOOLING = 3,
LayerType::kLRN = 4,
LayerType::kSCALE = 5,
LayerType::kSOFTMAX = 6,
LayerType::kDECONVOLUTION = 7,
LayerType::kCONCATENATION = 8,
LayerType::kELEMENTWISE = 9,
LayerType::kPLUGIN = 10,
LayerType::kRNN = 11,
LayerType::kUNARY = 12,
LayerType::kPADDING = 13,
LayerType::kSHUFFLE = 14,
LayerType::kREDUCE = 15,
LayerType::kTOPK = 16,
LayerType::kGATHER = 17,
LayerType::kMATRIX_MULTIPLY = 18,
LayerType::kRAGGED_SOFTMAX = 19,
LayerType::kCONSTANT = 20,
LayerType::kRNN_V2 = 21,
LayerType::kIDENTITY = 22,
LayerType::kPLUGIN_V2 = 23,
LayerType::kSLICE = 24,
LayerType::kSHAPE = 25,
LayerType::kPARAMETRIC_RELU = 26,
LayerType::kRESIZE = 27,
LayerType::kTRIP_LIMIT = 28,
LayerType::kRECURRENCE = 29,
LayerType::kITERATOR = 30,
LayerType::kLOOP_OUTPUT = 31,
LayerType::kSELECT = 32,
LayerType::kFILL = 33
} |
| | The type values of layer classes. More...
|
| |
| enum | PaddingMode : int32_t {
PaddingMode::kEXPLICIT_ROUND_DOWN = 0,
PaddingMode::kEXPLICIT_ROUND_UP = 1,
PaddingMode::kSAME_UPPER = 2,
PaddingMode::kSAME_LOWER = 3,
PaddingMode::kCAFFE_ROUND_DOWN = 4,
PaddingMode::kCAFFE_ROUND_UP = 5
} |
| | Enumerates the modes of padding to perform in convolution, deconvolution and pooling layer, padding mode takes precedence if setPaddingMode() and setPrePadding() are also used. More...
|
| |
| enum | PoolingType : int32_t {
PoolingType::kMAX = 0,
PoolingType::kAVERAGE = 1,
PoolingType::kMAX_AVERAGE_BLEND = 2
} |
| | The type of pooling to perform in a pooling layer. More...
|
| |
| enum | ScaleMode : int32_t {
ScaleMode::kUNIFORM = 0,
ScaleMode::kCHANNEL = 1,
ScaleMode::kELEMENTWISE = 2
} |
| | Controls how shift, scale and power are applied in a Scale layer. More...
|
| |
| enum | ElementWiseOperation : int32_t {
ElementWiseOperation::kSUM = 0,
ElementWiseOperation::kPROD = 1,
ElementWiseOperation::kMAX = 2,
ElementWiseOperation::kMIN = 3,
ElementWiseOperation::kSUB = 4,
ElementWiseOperation::kDIV = 5,
ElementWiseOperation::kPOW = 6,
ElementWiseOperation::kFLOOR_DIV = 7,
ElementWiseOperation::kAND = 8,
ElementWiseOperation::kOR = 9,
ElementWiseOperation::kXOR = 10,
ElementWiseOperation::kEQUAL = 11,
ElementWiseOperation::kGREATER = 12,
ElementWiseOperation::kLESS = 13
} |
| | Enumerates the binary operations that may be performed by an ElementWise layer. More...
|
| |
| enum | RNNOperation : int32_t {
RNNOperation::kRELU = 0,
RNNOperation::kTANH = 1,
RNNOperation::kLSTM = 2,
RNNOperation::kGRU = 3
} |
| | Enumerates the RNN operations that may be performed by an RNN layer. More...
|
| |
| enum | RNNDirection : int32_t {
RNNDirection::kUNIDIRECTION = 0,
RNNDirection::kBIDIRECTION = 1
} |
| | Enumerates the RNN direction that may be performed by an RNN layer. More...
|
| |
| enum | RNNInputMode : int32_t {
RNNInputMode::kLINEAR = 0,
RNNInputMode::kSKIP = 1
} |
| | Enumerates the RNN input modes that may occur with an RNN layer. More...
|
| |
| enum | RNNGateType : int32_t {
RNNGateType::kINPUT = 0,
RNNGateType::kOUTPUT = 1,
RNNGateType::kFORGET = 2,
RNNGateType::kUPDATE = 3,
RNNGateType::kRESET = 4,
RNNGateType::kCELL = 5,
RNNGateType::kHIDDEN = 6
} |
| | Identifies an individual gate within an RNN cell. More...
|
| |
| enum | UnaryOperation : int32_t {
UnaryOperation::kEXP = 0,
UnaryOperation::kLOG = 1,
UnaryOperation::kSQRT = 2,
UnaryOperation::kRECIP = 3,
UnaryOperation::kABS = 4,
UnaryOperation::kNEG = 5,
UnaryOperation::kSIN = 6,
UnaryOperation::kCOS = 7,
UnaryOperation::kTAN = 8,
UnaryOperation::kSINH = 9,
UnaryOperation::kCOSH = 10,
UnaryOperation::kASIN = 11,
UnaryOperation::kACOS = 12,
UnaryOperation::kATAN = 13,
UnaryOperation::kASINH = 14,
UnaryOperation::kACOSH = 15,
UnaryOperation::kATANH = 16,
UnaryOperation::kCEIL = 17,
UnaryOperation::kFLOOR = 18,
UnaryOperation::kERF = 19,
UnaryOperation::kNOT = 20
} |
| | Enumerates the unary operations that may be performed by a Unary layer. More...
|
| |
| enum | ReduceOperation : int32_t {
ReduceOperation::kSUM = 0,
ReduceOperation::kPROD = 1,
ReduceOperation::kMAX = 2,
ReduceOperation::kMIN = 3,
ReduceOperation::kAVG = 4
} |
| | Enumerates the reduce operations that may be performed by a Reduce layer. More...
|
| |
| enum | SliceMode : int32_t {
SliceMode::kDEFAULT = 0,
SliceMode::kWRAP = 1
} |
| | Controls how ISliceLayer handles out of bounds coordinates. More...
|
| |
| enum | TopKOperation : int32_t {
TopKOperation::kMAX = 0,
TopKOperation::kMIN = 1
} |
| | Enumerates the operations that may be performed by a TopK layer. More...
|
| |
| enum | MatrixOperation : int32_t {
MatrixOperation::kNONE,
MatrixOperation::kTRANSPOSE,
MatrixOperation::kVECTOR
} |
| | Enumerates the operations that may be performed on a tensor by IMatrixMultiplyLayer before multiplication. More...
|
| |
| enum | ResizeMode : int32_t {
ResizeMode::kNEAREST = 0,
ResizeMode::kLINEAR = 1
} |
| | Enumerates various modes of resize in the resize layer. Resize mode set using setResizeMode(). More...
|
| |
| enum | LoopOutput : int32_t {
LoopOutput::kLAST_VALUE = 0,
LoopOutput::kCONCATENATE = 1,
LoopOutput::kREVERSE = 2
} |
| | Enum that describes kinds of loop outputs. More...
|
| |
| enum | TripLimit : int32_t {
TripLimit::kCOUNT = 0,
TripLimit::kWHILE = 1
} |
| | Enum that describes kinds of trip limits. More...
|
| |
| enum | FillOperation : int32_t {
FillOperation::kLINSPACE = 0,
FillOperation::kRANDOM_UNIFORM = 1
} |
| | Enumerates the tensor fill operations that may performed by a fill layer. More...
|
| |
| enum | CalibrationAlgoType : int32_t {
CalibrationAlgoType::kLEGACY_CALIBRATION = 0,
CalibrationAlgoType::kENTROPY_CALIBRATION = 1,
CalibrationAlgoType::kENTROPY_CALIBRATION_2 = 2,
CalibrationAlgoType::kMINMAX_CALIBRATION = 3
} |
| | enum CalibrationAlgoType More...
|
| |
| enum | QuantizationFlag : int32_t { QuantizationFlag::kCALIBRATE_BEFORE_FUSION = 0
} |
| | List of valid flags for quantizing the network to int8. More...
|
| |
| enum | BuilderFlag : int32_t {
BuilderFlag::kFP16 = 0,
BuilderFlag::kINT8 = 1,
BuilderFlag::kDEBUG = 2,
BuilderFlag::kGPU_FALLBACK = 3,
BuilderFlag::kSTRICT_TYPES = 4,
BuilderFlag::kREFIT = 5,
BuilderFlag::kDISABLE_TIMING_CACHE = 6,
BuilderFlag::kTF32 = 7
} |
| | List of valid modes that the builder can enable when creating an engine from a network definition. More...
|
| |
| enum | ProfilingVerbosity : int32_t {
ProfilingVerbosity::kDEFAULT = 0,
ProfilingVerbosity::kNONE = 1,
ProfilingVerbosity::kVERBOSE = 2
} |
| | List of verbosity levels of layer information exposed in NVTX annotations. More...
|
| |
| enum | TacticSource : int32_t {
TacticSource::kCUBLAS = 0,
TacticSource::kCUBLAS_LT = 1
} |
| | List of tactic sources for TensorRT. More...
|
| |
| enum | NetworkDefinitionCreationFlag : int32_t {
NetworkDefinitionCreationFlag::kEXPLICIT_BATCH = 0,
NetworkDefinitionCreationFlag::kEXPLICIT_PRECISION = 1
} |
| | List of immutable network properties expressed at network creation time. NetworkDefinitionCreationFlag is used with createNetworkV2 to specify immutable properties of the network. The createNetwork() function always had an implicit batch dimension being specified by the maxBatchSize builder parameter. createNetworkV2 with kDEFAULT flag mimics that behaviour. More...
|
| |
| enum | PluginType : int32_t {
PluginType::kFASTERRCNN = 0,
PluginType::kNORMALIZE = 1,
PluginType::kPERMUTE = 2,
PluginType::kPRIORBOX = 3,
PluginType::kSSDDETECTIONOUTPUT = 4,
PluginType::kCONCAT = 5,
PluginType::kPRELU = 6,
PluginType::kYOLOREORG = 7,
PluginType::kYOLOREGION = 8,
PluginType::kANCHORGENERATOR = 9
} |
| | The type values for the various plugins. More...
|
| |
| enum | EngineCapability : int32_t {
EngineCapability::kDEFAULT = 0,
EngineCapability::kSAFE_GPU = 1,
EngineCapability::kSAFE_DLA = 2
} |
| | Forward declaration of IPluginFactory for use by other interfaces. More...
|
| |
| enum | DimensionOperation : int32_t {
DimensionOperation::kSUM = 0,
DimensionOperation::kPROD = 1,
DimensionOperation::kMAX = 2,
DimensionOperation::kMIN = 3,
DimensionOperation::kSUB = 4,
DimensionOperation::kEQUAL = 5,
DimensionOperation::kLESS = 6,
DimensionOperation::kFLOOR_DIV = 7,
DimensionOperation::kCEIL_DIV = 8
} |
| | An operation on two IDimensionExpr, which represent integer expressions used in dimension computations. More...
|
| |
| enum | WeightsRole : int32_t {
WeightsRole::kKERNEL = 0,
WeightsRole::kBIAS = 1,
WeightsRole::kSHIFT = 2,
WeightsRole::kSCALE = 3,
WeightsRole::kCONSTANT = 4
} |
| | How a layer uses particular Weights. More...
|
| |
| enum | DeviceType : int32_t {
DeviceType::kGPU,
DeviceType::kDLA
} |
| | The device that this layer/network will execute on. More...
|
| |
| enum | OptProfileSelector : int32_t {
OptProfileSelector::kMIN = 0,
OptProfileSelector::kOPT = 1,
OptProfileSelector::kMAX = 2
} |
| | When setting or querying optimization profile parameters (such as shape tensor inputs or dynamic dimensions), select whether we are interested in the minimum, optimum, or maximum values for these parameters. The minimum and maximum specify the permitted range that is supported at runtime, while the optimum value is used for the kernel selection. This should be the "typical" value that is expected to occur at runtime. More...
|
| |
| enum | ActivationType : int32_t {
ActivationType::kRELU = 0,
ActivationType::kSIGMOID = 1,
ActivationType::kTANH = 2,
ActivationType::kLEAKY_RELU = 3,
ActivationType::kELU = 4,
ActivationType::kSELU = 5,
ActivationType::kSOFTSIGN = 6,
ActivationType::kSOFTPLUS = 7,
ActivationType::kCLIP = 8,
ActivationType::kHARD_SIGMOID = 9,
ActivationType::kSCALED_TANH = 10,
ActivationType::kTHRESHOLDED_RELU = 11
} |
| | Enumerates the types of activation to perform in an activation layer. More...
|
| |
| enum | DataType : int32_t {
DataType::kFLOAT = 0,
DataType::kHALF = 1,
DataType::kINT8 = 2,
DataType::kINT32 = 3,
DataType::kBOOL = 4
} |
| | The type of weights and tensors. More...
|
| |
| enum | DimensionType : int32_t {
DimensionType::kSPATIAL = 0,
DimensionType::kCHANNEL = 1,
DimensionType::kINDEX = 2,
DimensionType::kSEQUENCE = 3
} |
| | The type of data encoded across this dimension. More...
|
| |
| enum | TensorFormat : int32_t {
TensorFormat::kLINEAR = 0,
TensorFormat::kNCHW = kLINEAR,
TensorFormat::kCHW2 = 1,
TensorFormat::kNC2HW2 = kCHW2,
TensorFormat::kHWC8 = 2,
TensorFormat::kNHWC8 = kHWC8,
TensorFormat::kCHW4 = 3,
TensorFormat::kCHW16 = 4,
TensorFormat::kCHW32 = 5,
TensorFormat::kDHWC8 = 6,
TensorFormat::kCDHW32 = 7,
TensorFormat::kHWC = 8,
TensorFormat::kDLA_LINEAR = 9,
TensorFormat::kDLA_HWC4 = 10
} |
| | Format of the input/output tensors. More...
|
| |
| enum | PluginVersion : uint8_t {
PluginVersion::kV2 = 0,
PluginVersion::kV2_EXT = 1,
PluginVersion::kV2_IOEXT = 2,
PluginVersion::kV2_DYNAMICEXT = 3
} |
| |
| enum | PluginFieldType : int32_t {
PluginFieldType::kFLOAT16 = 0,
PluginFieldType::kFLOAT32 = 1,
PluginFieldType::kFLOAT64 = 2,
PluginFieldType::kINT8 = 3,
PluginFieldType::kINT16 = 4,
PluginFieldType::kINT32 = 5,
PluginFieldType::kCHAR = 6,
PluginFieldType::kDIMS = 7,
PluginFieldType::kUNKNOWN = 8
} |
| |
| enum | TensorLocation : int32_t {
TensorLocation::kDEVICE = 0,
TensorLocation::kHOST = 1
} |
| | The location for tensor data storage, device or host. More...
|
| |
| enum | ErrorCode : int32_t {
ErrorCode::kSUCCESS = 0,
ErrorCode::kUNSPECIFIED_ERROR = 1,
ErrorCode::kINTERNAL_ERROR = 2,
ErrorCode::kINVALID_ARGUMENT = 3,
ErrorCode::kINVALID_CONFIG = 4,
ErrorCode::kFAILED_ALLOCATION = 5,
ErrorCode::kFAILED_INITIALIZATION = 6,
ErrorCode::kFAILED_EXECUTION = 7,
ErrorCode::kFAILED_COMPUTATION = 8,
ErrorCode::kINVALID_STATE = 9,
ErrorCode::kUNSUPPORTED_STATE = 10
} |
| | Error codes that can be returned by TensorRT during execution. More...
|
| |
The TensorRT API version 1 namespace.
1.8.17