Namespace List

Here is a list of all documented namespaces with brief descriptions:

[detail level 123]

►Nnvcaffeparser1	The TensorRT Caffe parser API namespace
CIBinaryProtoBlob	Object used to store and query data extracted from a binaryproto file using the ICaffeParser
CIBlobNameToTensor	Object used to store and query Tensors after they have been extracted from a Caffe model using the ICaffeParser
CICaffeParser	Class used for parsing Caffe models
CIPluginFactoryV2	Plugin factory used to configure plugins
►Nnvinfer1	The TensorRT API version 1 namespace
Nanonymous_namespace{NvInfer.h}
Nanonymous_namespace{NvInferRuntime.h}
►Napiv
CVConsistencyChecker
►Nconsistency
Nanonymous_namespace{NvInferConsistency.h}	Create an instance of an IConsistencyChecker class
CIConsistencyChecker	Validates a serialized engine blob
CIPluginChecker	Consistency Checker plugin class for user implemented Plugins
►Nimpl
CEnumMaxImpl	Declaration of EnumMaxImpl struct to store maximum number of elements in an enumeration type
CEnumMaxImpl< ActivationType >	Maximum number of elements in ActivationType enum
CEnumMaxImpl< AllocatorFlag >	Maximum number of elements in AllocatorFlag enum
CEnumMaxImpl< DataType >	Maximum number of elements in DataType enum
CEnumMaxImpl< ElementWiseOperation >	Maximum number of elements in ElementWiseOperation enum
CEnumMaxImpl< EngineCapability >	Maximum number of elements in EngineCapability enum
CEnumMaxImpl< ErrorCode >	Maximum number of elements in ErrorCode enum
CEnumMaxImpl< ILogger::Severity >	Maximum number of elements in ILogger::Severity enum
CEnumMaxImpl< PaddingMode >	Maximum number of elements in PaddingMode enum
CEnumMaxImpl< PoolingType >	Maximum number of elements in PoolingType enum
CEnumMaxImpl< ResizeCoordinateTransformation >	Maximum number of elements in ResizeCoordinateTransformation enum
CEnumMaxImpl< ResizeMode >	Maximum number of elements in ResizeMode enum
CEnumMaxImpl< ResizeRoundMode >	Maximum number of elements in ResizeRoundMode enum
CEnumMaxImpl< ResizeSelector >	Maximum number of elements in ResizeSelector enum
CEnumMaxImpl< TensorFormat >	Maximum number of elements in TensorFormat enum
CEnumMaxImpl< TensorLocation >	Maximum number of elements in TensorLocation enum
►Nplugin
CDetectionOutputParameters	The DetectionOutput plugin layer generates the detection output based on location and confidence predictions by doing non maximum suppression. This plugin first decodes the bounding boxes based on the anchors generated. It then performs non_max_suppression on the decoded bounding boxes. DetectionOutputParameters defines a set of parameters for creating the DetectionOutput plugin layer. It contains:
CGridAnchorParameters	The Anchor Generator plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W). GridAnchorParameters defines a set of parameters for creating the plugin layer for all feature maps. It contains:
CNMSParameters	The NMSParameters are used by the BatchedNMSPlugin for performing the non_max_suppression operation over boxes for object detection networks
CPriorBoxParameters	The PriorBox plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W). PriorBoxParameters defines a set of parameters for creating the PriorBox plugin layer. It contains:
CQuadruple	The Permute plugin layer permutes the input tensor by changing the memory order of the data. Quadruple defines a structure that contains an array of 4 integers. They can represent the permute orders or the strides in each dimension
CRegionParameters	The Region plugin layer performs region proposal calculation: generate 5 bounding boxes per cell (for yolo9000, generate 3 bounding boxes per cell). For each box, calculating its probablities of objects detections from 80 pre-defined classifications (yolo9000 has 9418 pre-defined classifications, and these 9418 items are organized as work-tree structure). RegionParameters defines a set of parameters for creating the Region plugin layer
CRPROIParams	RPROIParams is used to create the RPROIPlugin instance. It contains:
CsoftmaxTree	When performing yolo9000, softmaxTree is helping to do softmax on confidence scores, for element to get the precise classification through word-tree structured classification definition
Nutils
CDims2	Descriptor for two-dimensional data
CDims3	Descriptor for three-dimensional data
CDims32
CDims4	Descriptor for four-dimensional data
CDimsExprs
CDimsHW	Descriptor for two-dimensional spatial data
CDynamicPluginTensorDesc
CIActivationLayer	An Activation layer in a network definition
CIAlgorithm	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()."
CIAlgorithmContext	Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorithm
CIAlgorithmIOInfo	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()
CIAlgorithmSelector	Interface implemented by application for selecting and reporting algorithms of a layer provided by the builder
CIAlgorithmVariant	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()
CIAssertionLayer	An assertion layer in a network
CIBuilder	Builds an engine from a network definition
CIBuilderConfig	Holds properties for configuring a builder to produce an engine
CIConcatenationLayer	A concatenation layer in a network definition
CIConditionLayer
CIConstantLayer	Layer that represents a constant value
CIConvolutionLayer	A convolution layer in a network definition
CICudaEngine	An engine for executing inference on a built network, with functionally unsafe features
CIDeconvolutionLayer	A deconvolution layer in a network definition
CIDequantizeLayer	A Dequantize layer in a network definition
CIDimensionExpr
CIEinsumLayer	An Einsum layer in a network
CIElementWiseLayer	A elementwise layer in a network definition
CIEngineInspector	An engine inspector which prints out the layer information of an engine or an execution context
CIErrorRecorder	Reference counted application-implemented error reporting interface for TensorRT objects
CIExecutionContext	Context for executing inference using an engine, with functionally unsafe features
CIExprBuilder
CIFillLayer	Generate an output tensor with specified mode
CIFullyConnectedLayer	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:
CIGatherLayer	A Gather layer in a network definition. Supports several kinds of gathering
CIGpuAllocator	Application-implemented class for controlling allocation on the GPU
CIHostMemory	Class to handle library allocated memory that is accessible to the user
CIIdentityLayer	A layer that represents the identity function
CIIfConditional
CIIfConditionalBoundaryLayer
CIIfConditionalInputLayer
CIIfConditionalOutputLayer
CIInt8Calibrator	Application-implemented interface for calibration
CIInt8EntropyCalibrator
CIInt8EntropyCalibrator2
CIInt8LegacyCalibrator
CIInt8MinMaxCalibrator
CIIteratorLayer
CILayer	Base class for all layer classes in a network definition
CILogger	Application-implemented logging interface for the builder, refitter and runtime
CILoop
CILoopBoundaryLayer
CILoopOutputLayer
CILRNLayer	A LRN layer in a network definition
CIMatrixMultiplyLayer	Layer that represents a Matrix Multiplication
CINetworkDefinition	A network definition for input to the builder
CINoCopy	Forward declaration of IEngineInspector for use by other interfaces
CIOptimizationProfile	Optimization profile for dynamic input dimensions and shape tensors
CIPaddingLayer	Layer that represents a padding operation
CIParametricReLULayer	Layer that represents a parametric ReLU operation
CIPluginCreator	Plugin creator class for user implemented layers
CIPluginRegistry	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
CIPluginV2	Plugin class for user-implemented layers
CIPluginV2DynamicExt
CIPluginV2Ext	Plugin class for user-implemented layers
CIPluginV2IOExt	Plugin class for user-implemented layers
CIPluginV2Layer	Layer type for pluginV2
CIPoolingLayer	A Pooling layer in a network definition
CIProfiler	Application-implemented interface for profiling
CIQuantizeLayer	A Quantize layer in a network definition
CIRaggedSoftMaxLayer	A RaggedSoftmax layer in a network definition
CIRecurrenceLayer
CIReduceLayer	Layer that represents a reduction operator across Shape, Int32, Float, Half, and Int8 tensors
CIRefitter	Updates weights in an engine
CIResizeLayer	A resize layer in a network definition
CIRNNv2Layer	An RNN layer in a network definition, version 2
CIRuntime	Allows a serialized functionally unsafe engine to be deserialized
CIScaleLayer	A Scale layer in a network definition
CIScatterLayer	A scatter layer in a network definition. Supports several kinds of scattering
CISelectLayer
CIShapeLayer	Layer type for getting shape of a tensor
CIShuffleLayer	Layer type for shuffling data
CISliceLayer	Slices an input tensor into an output tensor based on the offset and strides
CISoftMaxLayer	A Softmax layer in a network definition
CITensor	A tensor in a network definition
CITimingCache	Class to handle tactic timing info collected from builder
CITopKLayer	Layer that represents a TopK reduction
CITripLimitLayer
CIUnaryLayer	Layer that represents an unary operation
CPermutation
CPluginField	Structure containing plugin attribute field names and associated data This information can be parsed to decode necessary plugin metadata
CPluginFieldCollection	Plugin field collection struct
CPluginRegistrar	Register the plugin creator to the registry The static registry object will be instantiated when the plugin library is loaded. This static object will register all creators available in the library to the registry
CPluginTensorDesc	Fields that a plugin might see for an input or output
CWeights	An array of weights used as a layer parameter
►Nnvonnxparser	The TensorRT ONNX parser API namespace
Nanonymous_namespace{NvOnnxParser.h}
CIOnnxConfig	Configuration Manager Class
CIParser	Object for parsing ONNX models into a TensorRT network definition
CIParserError	Object containing information about an error
►Nnvuffparser	The TensorRT UFF parser API namespace
CFieldCollection
CFieldMap	An array of field params used as a layer parameter for plugin layers
CIUffParser	Class used for parsing models described using the UFF format