|
| enum class | nvinfer1::LayerType : int32_t {
nvinfer1::kCONVOLUTION = 0
, nvinfer1::kCAST = 1
, nvinfer1::kACTIVATION = 2
, nvinfer1::kPOOLING = 3
,
nvinfer1::kLRN = 4
, nvinfer1::kSCALE = 5
, nvinfer1::kSOFTMAX = 6
, nvinfer1::kDECONVOLUTION = 7
,
nvinfer1::kCONCATENATION = 8
, nvinfer1::kELEMENTWISE = 9
, nvinfer1::kPLUGIN = 10
, nvinfer1::kUNARY = 11
,
nvinfer1::kPADDING = 12
, nvinfer1::kSHUFFLE = 13
, nvinfer1::kREDUCE = 14
, nvinfer1::kTOPK = 15
,
nvinfer1::kGATHER = 16
, nvinfer1::kMATRIX_MULTIPLY = 17
, nvinfer1::kRAGGED_SOFTMAX = 18
, nvinfer1::kCONSTANT = 19
,
nvinfer1::kIDENTITY = 20
, nvinfer1::kPLUGIN_V2 = 21
, nvinfer1::kSLICE = 22
, nvinfer1::kSHAPE = 23
,
nvinfer1::kPARAMETRIC_RELU = 24
, nvinfer1::kRESIZE = 25
, nvinfer1::kTRIP_LIMIT = 26
, nvinfer1::kRECURRENCE = 27
,
nvinfer1::kITERATOR = 28
, nvinfer1::kLOOP_OUTPUT = 29
, nvinfer1::kSELECT = 30
, nvinfer1::kFILL = 31
,
nvinfer1::kQUANTIZE = 32
, nvinfer1::kDEQUANTIZE = 33
, nvinfer1::kCONDITION = 34
, nvinfer1::kCONDITIONAL_INPUT = 35
,
nvinfer1::kCONDITIONAL_OUTPUT = 36
, nvinfer1::kSCATTER = 37
, nvinfer1::kEINSUM = 38
, nvinfer1::kASSERTION = 39
,
nvinfer1::kONE_HOT = 40
, nvinfer1::kNON_ZERO = 41
, nvinfer1::kGRID_SAMPLE = 42
, nvinfer1::kNMS = 43
,
nvinfer1::kREVERSE_SEQUENCE = 44
, nvinfer1::kNORMALIZATION = 45
, nvinfer1::kPLUGIN_V3 = 46
, nvinfer1::kSQUEEZE = 47
,
nvinfer1::kUNSQUEEZE = 48
, nvinfer1::kCUMULATIVE = 49
, nvinfer1::kDYNAMIC_QUANTIZE = 50
} |
| | The type values of layer classes. More...
|
| |
| enum class | nvinfer1::ActivationType : int32_t {
nvinfer1::kRELU = 0
, nvinfer1::kSIGMOID = 1
, nvinfer1::kTANH = 2
, nvinfer1::kLEAKY_RELU = 3
,
nvinfer1::kELU = 4
, nvinfer1::kSELU = 5
, nvinfer1::kSOFTSIGN = 6
, nvinfer1::kSOFTPLUS = 7
,
nvinfer1::kCLIP = 8
, nvinfer1::kHARD_SIGMOID = 9
, nvinfer1::kSCALED_TANH = 10
, nvinfer1::kTHRESHOLDED_RELU = 11
,
nvinfer1::kGELU_ERF = 12
, nvinfer1::kGELU_TANH = 13
} |
| | Enumerates the types of activation to perform in an activation layer. More...
|
| |
| enum class | nvinfer1::PaddingMode : int32_t { nvinfer1::kEXPLICIT_ROUND_DOWN = 0
, nvinfer1::kEXPLICIT_ROUND_UP = 1
, nvinfer1::kSAME_UPPER = 2
, nvinfer1::kSAME_LOWER = 3
} |
| | 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 class | nvinfer1::PoolingType : int32_t { nvinfer1::kMAX = 0
, nvinfer1::kAVERAGE = 1
, nvinfer1::kMAX_AVERAGE_BLEND = 2
} |
| | The type of pooling to perform in a pooling layer. More...
|
| |
| enum class | nvinfer1::ScaleMode : int32_t { nvinfer1::kUNIFORM = 0
, nvinfer1::kCHANNEL = 1
, nvinfer1::kELEMENTWISE = 2
} |
| | Controls how shift, scale and power are applied in a Scale layer. More...
|
| |
| enum class | nvinfer1::ElementWiseOperation : int32_t {
nvinfer1::kSUM = 0
, nvinfer1::kPROD = 1
, nvinfer1::kMAX = 2
, nvinfer1::kMIN = 3
,
nvinfer1::kSUB = 4
, nvinfer1::kDIV = 5
, nvinfer1::kPOW = 6
, nvinfer1::kFLOOR_DIV = 7
,
nvinfer1::kAND = 8
, nvinfer1::kOR = 9
, nvinfer1::kXOR = 10
, nvinfer1::kEQUAL = 11
,
nvinfer1::kGREATER = 12
, nvinfer1::kLESS = 13
} |
| | Enumerates the binary operations that may be performed by an ElementWise layer. More...
|
| |
| enum class | nvinfer1::GatherMode : int32_t { nvinfer1::kDEFAULT = 0
, nvinfer1::kELEMENT = 1
, nvinfer1::kND = 2
} |
| | Control form of IGatherLayer. More...
|
| |
| enum class | nvinfer1::UnaryOperation : int32_t {
nvinfer1::kEXP = 0
, nvinfer1::kLOG = 1
, nvinfer1::kSQRT = 2
, nvinfer1::kRECIP = 3
,
nvinfer1::kABS = 4
, nvinfer1::kNEG = 5
, nvinfer1::kSIN = 6
, nvinfer1::kCOS = 7
,
nvinfer1::kTAN = 8
, nvinfer1::kSINH = 9
, nvinfer1::kCOSH = 10
, nvinfer1::kASIN = 11
,
nvinfer1::kACOS = 12
, nvinfer1::kATAN = 13
, nvinfer1::kASINH = 14
, nvinfer1::kACOSH = 15
,
nvinfer1::kATANH = 16
, nvinfer1::kCEIL = 17
, nvinfer1::kFLOOR = 18
, nvinfer1::kERF = 19
,
nvinfer1::kNOT = 20
, nvinfer1::kSIGN = 21
, nvinfer1::kROUND = 22
, nvinfer1::kISINF = 23
,
nvinfer1::kISNAN = 24
} |
| | Enumerates the unary operations that may be performed by a Unary layer. More...
|
| |
| enum class | nvinfer1::ReduceOperation : int32_t {
nvinfer1::kSUM = 0
, nvinfer1::kPROD = 1
, nvinfer1::kMAX = 2
, nvinfer1::kMIN = 3
,
nvinfer1::kAVG = 4
} |
| | Enumerates the reduce operations that may be performed by a Reduce layer. More...
|
| |
| enum class | nvinfer1::SampleMode : int32_t {
nvinfer1::kSTRICT_BOUNDS = 0
, nvinfer1::kWRAP = 1
, nvinfer1::kCLAMP = 2
, nvinfer1::kFILL = 3
,
nvinfer1::kREFLECT = 4
} |
| | Controls how ISliceLayer and IGridSample handle out-of-bounds coordinates. More...
|
| |
| enum class | nvinfer1::TopKOperation : int32_t { nvinfer1::kMAX = 0
, nvinfer1::kMIN = 1
} |
| | Enumerates the operations that may be performed by a TopK layer. More...
|
| |
| enum class | nvinfer1::MatrixOperation : int32_t { nvinfer1::kNONE = 0
, nvinfer1::kTRANSPOSE = 1
, nvinfer1::kVECTOR = 2
} |
| | Enumerates the operations that may be performed on a tensor by IMatrixMultiplyLayer before multiplication. More...
|
| |
| enum class | nvinfer1::InterpolationMode : int32_t { nvinfer1::kNEAREST = 0
, nvinfer1::kLINEAR = 1
, nvinfer1::kCUBIC = 2
} |
| | Enumerates various modes of interpolation. More...
|
| |
| enum class | nvinfer1::ResizeCoordinateTransformation : int32_t { nvinfer1::kALIGN_CORNERS = 0
, nvinfer1::kASYMMETRIC = 1
, nvinfer1::kHALF_PIXEL = 2
} |
| | The resize coordinate transformation function. More...
|
| |
| enum class | nvinfer1::ResizeSelector : int32_t { nvinfer1::kFORMULA = 0
, nvinfer1::kUPPER = 1
} |
| | The coordinate selector when resize to single pixel output. More...
|
| |
| enum class | nvinfer1::ResizeRoundMode : int32_t { nvinfer1::kHALF_UP = 0
, nvinfer1::kHALF_DOWN = 1
, nvinfer1::kFLOOR = 2
, nvinfer1::kCEIL = 3
} |
| | The rounding mode for nearest neighbor resize. More...
|
| |
| enum class | nvinfer1::LoopOutput : int32_t { nvinfer1::kLAST_VALUE = 0
, nvinfer1::kCONCATENATE = 1
, nvinfer1::kREVERSE = 2
} |
| | Enum that describes kinds of loop outputs. More...
|
| |
| enum class | nvinfer1::TripLimit : int32_t { nvinfer1::kCOUNT = 0
, nvinfer1::kWHILE = 1
} |
| | Enum that describes kinds of trip limits. More...
|
| |
| enum class | nvinfer1::FillOperation : int32_t { nvinfer1::kLINSPACE = 0
, nvinfer1::kRANDOM_UNIFORM = 1
, nvinfer1::kRANDOM_NORMAL = 2
} |
| | Enumerates the tensor fill operations that may performed by a fill layer. More...
|
| |
| enum class | nvinfer1::ScatterMode : int32_t { nvinfer1::kELEMENT = 0
, nvinfer1::kND = 1
} |
| | Control form of IScatterLayer. More...
|
| |
| enum class | nvinfer1::BoundingBoxFormat : int32_t { nvinfer1::kCORNER_PAIRS = 0
, nvinfer1::kCENTER_SIZES = 1
} |
| | Representation of bounding box data used for the Boxes input tensor in INMSLayer. More...
|
| |
| enum class | nvinfer1::CumulativeOperation : int32_t { nvinfer1::kSUM = 0
} |
| | Enumerates the cumulative operations that may be performed by a Cumulative layer. More...
|
| |
| enum class | nvinfer1::CalibrationAlgoType : int32_t { nvinfer1::kLEGACY_CALIBRATION = 0
, nvinfer1::kENTROPY_CALIBRATION = 1
, nvinfer1::kENTROPY_CALIBRATION_2 = 2
, nvinfer1::kMINMAX_CALIBRATION = 3
} |
| | Version of calibration algorithm to use. More...
|
| |
| enum class | nvinfer1::QuantizationFlag : int32_t { nvinfer1::kCALIBRATE_BEFORE_FUSION = 0
} |
| | List of valid flags for quantizing the network to int8. More...
|
| |
| enum class | nvinfer1::RuntimePlatform : int32_t { nvinfer1::kSAME_AS_BUILD = 0
, nvinfer1::kWINDOWS_AMD64 = 1
} |
| | Describes the intended runtime platform (operating system and CPU architecture) for the execution of the TensorRT engine. TensorRT provides support for cross-platform engine compatibility when the target runtime platform is different from the build platform. More...
|
| |
| enum class | nvinfer1::BuilderFlag : int32_t {
nvinfer1::kFP16 = 0
, nvinfer1::kINT8 = 1
, nvinfer1::kDEBUG = 2
, nvinfer1::kGPU_FALLBACK = 3
,
nvinfer1::kREFIT = 4
, nvinfer1::kDISABLE_TIMING_CACHE = 5
, nvinfer1::kTF32 = 6
, nvinfer1::kSPARSE_WEIGHTS = 7
,
nvinfer1::kSAFETY_SCOPE = 8
, nvinfer1::kOBEY_PRECISION_CONSTRAINTS = 9
, nvinfer1::kPREFER_PRECISION_CONSTRAINTS = 10
, nvinfer1::kDIRECT_IO = 11
,
nvinfer1::kREJECT_EMPTY_ALGORITHMS = 12
, nvinfer1::kVERSION_COMPATIBLE = 13
, nvinfer1::kEXCLUDE_LEAN_RUNTIME = 14
, nvinfer1::kFP8 = 15
,
nvinfer1::kERROR_ON_TIMING_CACHE_MISS = 16
, nvinfer1::kBF16 = 17
, nvinfer1::kDISABLE_COMPILATION_CACHE = 18
, nvinfer1::kSTRIP_PLAN = 19
,
nvinfer1::kWEIGHTLESS = kSTRIP_PLAN
, nvinfer1::kREFIT_IDENTICAL = 20
, nvinfer1::kWEIGHT_STREAMING = 21
, nvinfer1::kINT4 = 22
,
nvinfer1::kREFIT_INDIVIDUAL = 23
, nvinfer1::kSTRICT_NANS = 24
, nvinfer1::kMONITOR_MEMORY = 25
, nvinfer1::kFP4 = 26
,
nvinfer1::kEDITABLE_TIMING_CACHE = 27
} |
| | List of valid modes that the builder can enable when creating an engine from a network definition. More...
|
| |
| enum class | nvinfer1::MemoryPoolType : int32_t {
nvinfer1::kWORKSPACE = 0
, nvinfer1::kDLA_MANAGED_SRAM = 1
, nvinfer1::kDLA_LOCAL_DRAM = 2
, nvinfer1::kDLA_GLOBAL_DRAM = 3
,
nvinfer1::kTACTIC_DRAM = 4
, nvinfer1::kTACTIC_SHARED_MEMORY = 5
} |
| | The type for memory pools used by TensorRT. More...
|
| |
| enum class | nvinfer1::PreviewFeature : int32_t { nvinfer1::kPROFILE_SHARING_0806 = 0
, nvinfer1::kALIASED_PLUGIN_IO_10_03 = 1
, nvinfer1::kRUNTIME_ACTIVATION_RESIZE_10_10 = 2
} |
| | Define preview features. More...
|
| |
| enum class | nvinfer1::HardwareCompatibilityLevel : int32_t { nvinfer1::kNONE = 0
, nvinfer1::kAMPERE_PLUS = 1
, nvinfer1::kSAME_COMPUTE_CAPABILITY = 2
} |
| | Describes requirements of compatibility with GPU architectures other than that of the GPU on which the engine was built. More...
|
| |
| enum class | nvinfer1::TilingOptimizationLevel : int32_t { nvinfer1::kNONE = 0
, nvinfer1::kFAST = 1
, nvinfer1::kMODERATE = 2
, nvinfer1::kFULL = 3
} |
| | Define the optimization levels for Tiling. More...
|
| |
| enum class | nvinfer1::NetworkDefinitionCreationFlag : int32_t { nvinfer1::kEXPLICIT_BATCH = 0
, nvinfer1::kSTRONGLY_TYPED = 1
, nvinfer1::kPREFER_JIT_PYTHON_PLUGINS = 2
, nvinfer1::kPREFER_AOT_PYTHON_PLUGINS = 3
} |
| | List of immutable network properties expressed at network creation time. NetworkDefinitionCreationFlag is used with createNetworkV2() to specify immutable properties of the network. More...
|
| |
This is the top-level API file for TensorRT.
1.9.2