Class Hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 1234]

Cnvinfer1::plugin::DetectionOutputParameters	The DetectionOutput plugin layer generates the detection output based on location and confidence predictions by doing non maximum suppression
CDims	Structure to define the dimensions of a tensor
▼Cnvinfer1::Dims64
▼Cnvinfer1::Dims2	Descriptor for two-dimensional data
▼Cnvinfer1::Dims3	Descriptor for three-dimensional data
Cnvinfer1::Dims4	Descriptor for four-dimensional data
Cnvinfer1::DimsHW	Descriptor for two-dimensional spatial data
Cnvinfer1::DimsExprs	Analog of class Dims with expressions instead of constants for the dimensions
Cnvinfer1::DynamicPluginTensorDesc	Summarizes tensors that a plugin might see for an input or output
Cnvinfer1::impl::EnumMaxImpl< T >	Declaration of EnumMaxImpl struct to store maximum number of elements in an enumeration type
Cnvinfer1::impl::EnumMaxImpl< ActivationType >
Cnvinfer1::impl::EnumMaxImpl< AllocatorFlag >	Maximum number of elements in AllocatorFlag enum
Cnvinfer1::impl::EnumMaxImpl< APILanguage >	Maximum number of elements in APILanguage enum
Cnvinfer1::impl::EnumMaxImpl< CumulativeOperation >	Maximum number of elements in CumulativeOperation enum
Cnvinfer1::impl::EnumMaxImpl< DataType >	Maximum number of elements in DataType enum
Cnvinfer1::impl::EnumMaxImpl< ElementWiseOperation >
Cnvinfer1::impl::EnumMaxImpl< EngineCapability >	Maximum number of elements in EngineCapability enum
Cnvinfer1::impl::EnumMaxImpl< ErrorCode >	Maximum number of elements in ErrorCode enum
Cnvinfer1::impl::EnumMaxImpl< HardwareCompatibilityLevel >
Cnvinfer1::impl::EnumMaxImpl< ILogger::Severity >	Maximum number of elements in ILogger::Severity enum
Cnvinfer1::impl::EnumMaxImpl< InterpolationMode >
Cnvinfer1::impl::EnumMaxImpl< PaddingMode >
Cnvinfer1::impl::EnumMaxImpl< PoolingType >
Cnvinfer1::impl::EnumMaxImpl< PreviewFeature >
Cnvinfer1::impl::EnumMaxImpl< ResizeCoordinateTransformation >
Cnvinfer1::impl::EnumMaxImpl< ResizeRoundMode >
Cnvinfer1::impl::EnumMaxImpl< ResizeSelector >
Cnvinfer1::impl::EnumMaxImpl< RuntimePlatform >
Cnvinfer1::impl::EnumMaxImpl< TensorFormat >	Maximum number of elements in TensorFormat enum
Cnvinfer1::impl::EnumMaxImpl< TensorIOMode >	Maximum number of elements in TensorIOMode enum
Cnvinfer1::impl::EnumMaxImpl< TensorLocation >	Maximum number of elements in TensorLocation enum
Cnvinfer1::impl::EnumMaxImpl< TilingOptimizationLevel >
Cnvinfer1::plugin::GridAnchorParameters	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
CIAlgorithmSelector	Interface implemented by application for selecting and reporting algorithms of a layer provided by the builder
CIDebugListener	User-implemented callback for notification when value of a debug tensor is updated
CIErrorRecorder	Reference counted application-implemented error reporting interface for TensorRT objects
CIGpuAllocator	Application-implemented class for controlling allocation on the GPU
CIGpuAsyncAllocator	Application-implemented class for controlling asynchronous (stream ordered) memory allocation on the GPU
CIInt8EntropyCalibrator	Entropy calibrator
CIInt8EntropyCalibrator2	Entropy calibrator 2
CIInt8LegacyCalibrator	Legacy calibrator
CIInt8MinMaxCalibrator	MinMax Calibrator
Cnvinfer1::ILogger	Application-implemented logging interface for the builder, refitter and runtime
Cnvinfer1::ILoggerFinder	A virtual base class to find a logger. Allows a plugin to find an instance of a logger if it needs to emit a log message. A pointer to an instance of this class is passed to a plugin shared library on initialization when that plugin is serialized as part of a version-compatible plan. See the plugin chapter in the developer guide for details
▼Cnvinfer1::INoCopy	Forward declaration of IEngineInspector for use by other interfaces
Cnvinfer1::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()
Cnvinfer1::IAlgorithmContext	Describes the context and requirements, that could be fulfilled by one or more instances of IAlgorithm
Cnvinfer1::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()
Cnvinfer1::IAlgorithmVariant	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()
Cnvinfer1::IBuilder	Builds an engine from a network definition
Cnvinfer1::IBuilderConfig	Holds properties for configuring a builder to produce an engine
Cnvinfer1::ICudaEngine	An engine for executing inference on a built network, with functionally unsafe features
Cnvinfer1::IDimensionExpr	An IDimensionExpr represents an integer expression constructed from constants, input dimensions, and binary operations. These expressions are can be used in overrides of IPluginV2DynamicExt::getOutputDimensions or IPluginV3OneBuild::getOutputShapes() to define output dimensions in terms of input dimensions
Cnvinfer1::IEngineInspector	An engine inspector which prints out the layer information of an engine or an execution context
Cnvinfer1::IExecutionContext	Context for executing inference using an engine, with functionally unsafe features
Cnvinfer1::IExprBuilder	Object for constructing IDimensionExpr
Cnvinfer1::IHostMemory	Class to handle library allocated memory that is accessible to the user
Cnvinfer1::IIfConditional	Helper for constructing conditionally-executed subgraphs
▼Cnvinfer1::ILayer	Base class for all layer classes in a network definition
Cnvinfer1::IActivationLayer	An Activation layer in a network definition
Cnvinfer1::IAssertionLayer	An assertion layer in a network
Cnvinfer1::ICastLayer	A cast layer in a network
Cnvinfer1::IConcatenationLayer	A concatenation layer in a network definition
Cnvinfer1::IConstantLayer	Layer that represents a constant value
Cnvinfer1::IConvolutionLayer	A convolution layer in a network definition
Cnvinfer1::ICumulativeLayer	Layer that represents a cumulative operation across a tensor
Cnvinfer1::IDeconvolutionLayer	A deconvolution layer in a network definition
Cnvinfer1::IDequantizeLayer	A Dequantize layer in a network definition
Cnvinfer1::IDynamicQuantizeLayer	A network layer to perform dynamic quantization
Cnvinfer1::IEinsumLayer	An Einsum layer in a network
Cnvinfer1::IElementWiseLayer	A elementwise layer in a network definition
Cnvinfer1::IFillLayer	Generate a tensor according to a specified mode
Cnvinfer1::IGatherLayer	A Gather layer in a network definition. Supports several kinds of gathering
Cnvinfer1::IGridSampleLayer	A GridSample layer in a network definition
Cnvinfer1::IIdentityLayer	A layer that represents the identity function
▼Cnvinfer1::IIfConditionalBoundaryLayer	This is a base class for Conditional boundary layers
Cnvinfer1::IConditionLayer	This layer represents a condition input to an IIfConditional
Cnvinfer1::IIfConditionalInputLayer	This layer represents an input to an IIfConditional
Cnvinfer1::IIfConditionalOutputLayer	This layer represents an output of an IIfConditional
Cnvinfer1::ILRNLayer	A LRN layer in a network definition
▼Cnvinfer1::ILoopBoundaryLayer	This is a base class for Loop boundary layers
Cnvinfer1::IIteratorLayer	A layer to do iterations
Cnvinfer1::ILoopOutputLayer	An ILoopOutputLayer is the sole way to get output from a loop
Cnvinfer1::IRecurrenceLayer	A recurrence layer in a network definition
Cnvinfer1::ITripLimitLayer	A layer that represents a trip-count limiter
Cnvinfer1::IMatrixMultiplyLayer	Layer that represents a Matrix Multiplication
Cnvinfer1::INMSLayer	A non-maximum suppression layer in a network definition
Cnvinfer1::INonZeroLayer
Cnvinfer1::INormalizationLayer	A normalization layer in a network definition
Cnvinfer1::IOneHotLayer	A OneHot layer in a network definition
Cnvinfer1::IPaddingLayer	Layer that represents a padding operation
Cnvinfer1::IParametricReLULayer	Layer that represents a parametric ReLU operation
Cnvinfer1::IPluginV2Layer	Layer type for pluginV2
Cnvinfer1::IPluginV3Layer	Layer type for V3 plugins
Cnvinfer1::IPoolingLayer	A Pooling layer in a network definition
Cnvinfer1::IQuantizeLayer	A Quantize layer in a network definition
Cnvinfer1::IRaggedSoftMaxLayer	A RaggedSoftmax layer in a network definition
Cnvinfer1::IReduceLayer	Layer that represents a reduction across a non-bool tensor
Cnvinfer1::IResizeLayer	A resize layer in a network definition
Cnvinfer1::IReverseSequenceLayer	A ReverseSequence layer in a network definition
Cnvinfer1::IScaleLayer	A Scale layer in a network definition
Cnvinfer1::IScatterLayer	A scatter layer in a network definition. Supports several kinds of scattering
Cnvinfer1::ISelectLayer	Select elements from two data tensors based on a condition tensor
Cnvinfer1::IShapeLayer	Layer type for getting shape of a tensor
Cnvinfer1::IShuffleLayer	Layer type for shuffling data
Cnvinfer1::ISliceLayer	Slices an input tensor into an output tensor based on the offset and strides
Cnvinfer1::ISoftMaxLayer	A Softmax layer in a network definition
Cnvinfer1::ISqueezeLayer	Layer that represents a squeeze operation, removing unit dimensions of the input tensor on a set of axes
Cnvinfer1::ITopKLayer	Layer that represents a TopK reduction
Cnvinfer1::IUnaryLayer	Layer that represents an unary operation
Cnvinfer1::IUnsqueezeLayer	Layer that represents an unsqueeze operation, which reshapes the input tensor by inserting unit-length dimensions at specified axes of the output
Cnvinfer1::ILoop	Helper for creating a recurrent subgraph
Cnvinfer1::INetworkDefinition	A network definition for input to the builder
Cnvinfer1::IOptimizationProfile	Optimization profile for dynamic input dimensions and shape tensors
Cnvinfer1::IRefitter	Updates weights in an engine
Cnvinfer1::IRuntime	Allows a serialized functionally unsafe engine to be deserialized
Cnvinfer1::IRuntimeConfig	A class for runtime configuration. This class is used during execution context creation
Cnvinfer1::ISerializationConfig	Holds properties for configuring an engine to serialize the binary
Cnvinfer1::ITensor	A tensor in a network definition
Cnvinfer1::ITimingCache	Class to handle tactic timing info collected from builder
CINonZero	A NonZero layer in a network
Cnvinfer1::InterfaceInfo	Version information associated with a TRT interface
Cnvonnxparser::IOnnxConfig	Configuration Manager Class
CIOutputAllocator	Callback from ExecutionContext::enqueueV3()
Cnvonnxparser::IParser	Object for parsing ONNX models into a TensorRT network definition
Cnvonnxparser::IParserError	Object containing information about an error
Cnvonnxparser::IParserRefitter	An interface designed to refit weights from an ONNX model
CIPluginCapability	Base class for plugin capability interfaces
CIPluginCreator	Plugin creator class for user implemented layers
CIPluginCreatorInterface	Base class for all plugin creator versions
CIPluginCreatorV3One	A plugin creator class capable of producing IPluginV3 objects
Cnvinfer1::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
CIPluginResource	Interface for plugins to define custom resources that could be shared through the plugin registry
Cnvinfer1::IPluginResourceContext	Interface for plugins to access per context resources provided by TensorRT
▼Cnvinfer1::IPluginV2	Plugin class for user-implemented layers
▼Cnvinfer1::IPluginV2Ext	Plugin class for user-implemented layers
Cnvinfer1::IPluginV2DynamicExt	Similar to IPluginV2Ext, but with support for dynamic shapes
Cnvinfer1::IPluginV2IOExt	Plugin class for user-implemented layers
CIPluginV3	Plugin class for the V3 generation of user-implemented layers
CIPluginV3OneBuild	A plugin capability interface that enables the build capability (PluginCapabilityType::kBUILD). Exposes methods that allow the expression of the build time properties and behavior of a plugin
CIPluginV3OneBuildV2	A plugin capability interface that extends IPluginV3OneBuild by providing I/O aliasing functionality
CIPluginV3OneCore	A plugin capability interface that enables the core capability (PluginCapabilityType::kCORE)
CIPluginV3OneRuntime	A plugin capability interface that enables the runtime capability (PluginCapabilityType::kRUNTIME). Exposes methods that allow the expression of the runtime properties and behavior of a plugin
CIProfiler	Application-implemented interface for profiling
Cnvinfer1::v_1_0::IProfiler
CIProgressMonitor	Application-implemented progress reporting interface for TensorRT
▼Cnvinfer2::safe::ISafeRecorder
Cparser::ParserSafeRecorder	The ParserSafeRecorder implementation of the ISafeRecorder interface
CIStreamReader	Application-implemented class for reading data in a stream-based manner
CIStreamReaderV2	Application-implemented class for reading data in a stream-based manner asynchronously. Intended for use with the GDS API for optimizing load times
▼Cnvinfer1::IVersionedInterface	An Interface class for version control
▼Cnvinfer1::IInt8Calibrator	Application-implemented interface for calibration
Cnvinfer1::v_1_0::IInt8EntropyCalibrator
Cnvinfer1::v_1_0::IInt8EntropyCalibrator2
Cnvinfer1::v_1_0::IInt8LegacyCalibrator
Cnvinfer1::v_1_0::IInt8MinMaxCalibrator
Cnvinfer1::v_1_0::IAlgorithmSelector
Cnvinfer1::v_1_0::IDebugListener
Cnvinfer1::v_1_0::IErrorRecorder
▼Cnvinfer1::v_1_0::IGpuAllocator
Cnvinfer1::v_1_0::IGpuAsyncAllocator
Cnvinfer1::v_1_0::IOutputAllocator
▼Cnvinfer1::v_1_0::IPluginCapability
▼Cnvinfer1::v_1_0::IPluginV3OneBuild
Cnvinfer1::v_2_0::IPluginV3OneBuild
Cnvinfer1::v_1_0::IPluginV3OneCore
Cnvinfer1::v_1_0::IPluginV3OneRuntime
▼Cnvinfer1::v_1_0::IPluginCreatorInterface
Cnvinfer1::v_1_0::IPluginCreator
Cnvinfer1::v_1_0::IPluginCreatorV3One
Cnvinfer1::v_1_0::IPluginResource
Cnvinfer1::v_1_0::IPluginV3
Cnvinfer1::v_1_0::IProgressMonitor
Cnvinfer1::v_1_0::IStreamReader
Cnvinfer1::v_1_0::IStreamReaderV2
Cnvinfer1::plugin::NMSParameters	The NMSParameters are used by the BatchedNMSPlugin for performing the non_max_suppression operation over boxes for object detection networks
Cnvinfer1::Permutation	Represents a permutation of dimensions
Cnvinfer1::PluginField	Structure containing plugin attribute field names and associated data This information can be parsed to decode necessary plugin metadata
Cnvinfer1::PluginFieldCollection	Plugin field collection struct
Cnvinfer1::PluginRegistrar< T >	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
Cnvinfer1::PluginTensorDesc	Fields that a plugin might see for an input or output
CPluginVersion	Definition of plugin versions
Cnvinfer1::plugin::PriorBoxParameters	The PriorBox plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W)
Cnvinfer1::plugin::RegionParameters	The Region plugin layer performs region proposal calculation
Cnvinfer1::plugin::RPROIParams	RPROIParams is used to create the RPROIPlugin instance
Cnvinfer1::plugin::softmaxTree	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
Cnvinfer1::v_1_0::TimingCacheKey	The key to retrieve timing cache entries
Cnvinfer1::v_1_0::TimingCacheValue
CValue	The values in the cache entry
Cnvinfer1::Weights	An array of weights used as a layer parameter