TensorRT 10.0.0
Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1234]
 Cnvinfer1::plugin::DetectionOutputParametersThe DetectionOutput plugin layer generates the detection output based on location and confidence predictions by doing non maximum suppression
 CDimsStructure to define the dimensions of a tensor
 Cnvinfer1::Dims64
 Cnvinfer1::Dims2Descriptor for two-dimensional data
 Cnvinfer1::Dims3Descriptor for three-dimensional data
 Cnvinfer1::Dims4Descriptor for four-dimensional data
 Cnvinfer1::DimsHWDescriptor for two-dimensional spatial data
 Cnvinfer1::DimsExprsAnalog of class Dims with expressions instead of constants for the dimensions
 Cnvinfer1::DynamicPluginTensorDescSummarizes 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< 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< 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::plugin::GridAnchorParametersThe 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
 CIAlgorithmSelectorInterface implemented by application for selecting and reporting algorithms of a layer provided by the builder
 Cnvinfer1::consistency::IConsistencyCheckerValidates a serialized engine blob
 Cnvinfer1::safe::ICudaEngineA functionally safe engine for executing inference on a built network
 CIDebugListenerUser-implemented callback for notification when value of a debug tensor is updated
 CIErrorRecorderReference counted application-implemented error reporting interface for TensorRT objects
 Cnvinfer1::safe::IExecutionContextFunctionally safe context for executing inference using an engine
 CIGpuAllocatorApplication-implemented class for controlling allocation on the GPU
 CIGpuAsyncAllocatorApplication-implemented class for controlling asynchronous (stream ordered) memory allocation on the GPU
 CIInt8EntropyCalibratorEntropy calibrator
 CIInt8EntropyCalibrator2Entropy calibrator 2
 CIInt8LegacyCalibratorLegacy calibrator
 CIInt8MinMaxCalibratorMinMax Calibrator
 Cnvinfer1::ILoggerApplication-implemented logging interface for the builder, refitter and runtime
 Cnvinfer1::ILoggerFinderA 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::INoCopyForward declaration of IEngineInspector for use by other interfaces
 Cnvinfer1::IAlgorithmDescribes 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::IAlgorithmContextDescribes the context and requirements, that could be fulfilled by one or more instances of IAlgorithm
 Cnvinfer1::IAlgorithmIOInfoCarries 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::IAlgorithmVariantUnique 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::IBuilderBuilds an engine from a network definition
 Cnvinfer1::IBuilderConfigHolds properties for configuring a builder to produce an engine
 Cnvinfer1::ICudaEngineAn engine for executing inference on a built network, with functionally unsafe features
 Cnvinfer1::IDimensionExprAn 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::IEngineInspectorAn engine inspector which prints out the layer information of an engine or an execution context
 Cnvinfer1::IExecutionContextContext for executing inference using an engine, with functionally unsafe features
 Cnvinfer1::IExprBuilderObject for constructing IDimensionExpr
 Cnvinfer1::IHostMemoryClass to handle library allocated memory that is accessible to the user
 Cnvinfer1::IIfConditionalHelper for constructing conditionally-executed subgraphs
 Cnvinfer1::ILayerBase class for all layer classes in a network definition
 Cnvinfer1::IActivationLayerAn Activation layer in a network definition
 Cnvinfer1::IAssertionLayerAn assertion layer in a network
 Cnvinfer1::ICastLayerA cast layer in a network
 Cnvinfer1::IConcatenationLayerA concatenation layer in a network definition
 Cnvinfer1::IConstantLayerLayer that represents a constant value
 Cnvinfer1::IConvolutionLayerA convolution layer in a network definition
 Cnvinfer1::IDeconvolutionLayerA deconvolution layer in a network definition
 Cnvinfer1::IDequantizeLayerA Dequantize layer in a network definition
 Cnvinfer1::IEinsumLayerAn Einsum layer in a network
 Cnvinfer1::IElementWiseLayerA elementwise layer in a network definition
 Cnvinfer1::IFillLayerGenerate a tensor according to a specified mode
 Cnvinfer1::IGatherLayerA Gather layer in a network definition. Supports several kinds of gathering
 Cnvinfer1::IGridSampleLayerA GridSample layer in a network definition
 Cnvinfer1::IIdentityLayerA layer that represents the identity function
 Cnvinfer1::IIfConditionalBoundaryLayerThis is a base class for Conditional boundary layers
 Cnvinfer1::IConditionLayerThis layer represents a condition input to an IIfConditional
 Cnvinfer1::IIfConditionalInputLayerThis layer represents an input to an IIfConditional
 Cnvinfer1::IIfConditionalOutputLayerThis layer represents an output of an IIfConditional
 Cnvinfer1::ILRNLayerA LRN layer in a network definition
 Cnvinfer1::ILoopBoundaryLayerThis is a base class for Loop boundary layers
 Cnvinfer1::IIteratorLayerA layer to do iterations
 Cnvinfer1::ILoopOutputLayerAn ILoopOutputLayer is the sole way to get output from a loop
 Cnvinfer1::IRecurrenceLayerA recurrence layer in a network definition
 Cnvinfer1::ITripLimitLayerA layer that represents a trip-count limiter
 Cnvinfer1::IMatrixMultiplyLayerLayer that represents a Matrix Multiplication
 Cnvinfer1::INMSLayerA non-maximum suppression layer in a network definition
 Cnvinfer1::INonZeroLayer
 Cnvinfer1::INormalizationLayerA normalization layer in a network definition
 Cnvinfer1::IOneHotLayerA OneHot layer in a network definition
 Cnvinfer1::IPaddingLayerLayer that represents a padding operation
 Cnvinfer1::IParametricReLULayerLayer that represents a parametric ReLU operation
 Cnvinfer1::IPluginV2LayerLayer type for pluginV2
 Cnvinfer1::IPluginV3LayerLayer type for V3 plugins
 Cnvinfer1::IPoolingLayerA Pooling layer in a network definition
 Cnvinfer1::IQuantizeLayerA Quantize layer in a network definition
 Cnvinfer1::IRaggedSoftMaxLayerA RaggedSoftmax layer in a network definition
 Cnvinfer1::IReduceLayerLayer that represents a reduction across a non-bool tensor
 Cnvinfer1::IResizeLayerA resize layer in a network definition
 Cnvinfer1::IReverseSequenceLayerA ReverseSequence layer in a network definition
 Cnvinfer1::IScaleLayerA Scale layer in a network definition
 Cnvinfer1::IScatterLayerA scatter layer in a network definition. Supports several kinds of scattering
 Cnvinfer1::ISelectLayerA select layer in a network definition
 Cnvinfer1::IShapeLayerLayer type for getting shape of a tensor
 Cnvinfer1::IShuffleLayerLayer type for shuffling data
 Cnvinfer1::ISliceLayerSlices an input tensor into an output tensor based on the offset and strides
 Cnvinfer1::ISoftMaxLayerA Softmax layer in a network definition
 Cnvinfer1::ITopKLayerLayer that represents a TopK reduction
 Cnvinfer1::IUnaryLayerLayer that represents an unary operation
 Cnvinfer1::ILoopHelper for creating a recurrent subgraph
 Cnvinfer1::INetworkDefinitionA network definition for input to the builder
 Cnvinfer1::IOptimizationProfileOptimization profile for dynamic input dimensions and shape tensors
 Cnvinfer1::IRefitterUpdates weights in an engine
 Cnvinfer1::IRuntimeAllows a serialized functionally unsafe engine to be deserialized
 Cnvinfer1::ISerializationConfigHolds properties for configuring an engine to serialize the binary
 Cnvinfer1::ITensorA tensor in a network definition
 Cnvinfer1::ITimingCacheClass to handle tactic timing info collected from builder
 CINonZeroA NonZero layer in a network
 Cnvinfer1::InterfaceInfoVersion information associated with a TRT interface
 Cnvonnxparser::IOnnxConfigConfiguration Manager Class
 CIOutputAllocatorCallback from ExecutionContext::enqueueV3()
 Cnvonnxparser::IParserObject for parsing ONNX models into a TensorRT network definition
 Cnvonnxparser::IParserErrorObject containing information about an error
 Cnvonnxparser::IParserRefitterAn interface designed to refit weights from an ONNX model
 CIPluginCapabilityBase class for plugin capability interfaces
 CIPluginCreatorPlugin creator class for user implemented layers
 CIPluginCreatorInterfaceBase class for all plugin creator versions
 CIPluginCreatorV3OneA plugin creator class capable of producing IPluginV3 objects
 Cnvinfer1::IPluginRegistrySingle 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
 Cnvinfer1::safe::IPluginRegistrySingle 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 must also have a corresponding IPluginCreator implementation
 CIPluginResourceInterface for plugins to define custom resources that could be shared through the plugin registry
 Cnvinfer1::IPluginResourceContextInterface for plugins to access per context resources provided by TensorRT
 Cnvinfer1::IPluginV2Plugin class for user-implemented layers
 Cnvinfer1::IPluginV2ExtPlugin class for user-implemented layers
 Cnvinfer1::IPluginV2DynamicExtSimilar to IPluginV2Ext, but with support for dynamic shapes
 Cnvinfer1::IPluginV2IOExtPlugin class for user-implemented layers
 CIPluginV3Plugin class for the V3 generation of user-implemented layers
 CIPluginV3OneBuildA 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
 CIPluginV3OneCoreA plugin capability interface that enables the core capability (PluginCapabilityType::kCORE)
 CIPluginV3OneRuntimeA 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
 CIProfilerApplication-implemented interface for profiling
 Cnvinfer1::v_1_0::IProfiler
 CIProgressMonitorApplication-implemented progress reporting interface for TensorRT
 Cnvinfer1::safe::IRuntimeAllows a serialized functionally safe engine to be deserialized
 CIStreamReaderApplication-implemented class for reading data in a stream-based manner
 Cnvinfer1::IVersionedInterfaceAn Interface class for version control
 Cnvinfer1::IInt8CalibratorApplication-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_1_0::IPluginV3OneCore
 Cnvinfer1::v_1_0::IPluginV3OneRuntime
 Cnvinfer1::v_1_0::IPluginCreatorInterface
 Cnvinfer1::v_1_0::IPluginCreator
 Cnvinfer1::consistency::IPluginCheckerConsistency Checker plugin class for user implemented Plugins
 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::plugin::NMSParametersThe NMSParameters are used by the BatchedNMSPlugin for performing the non_max_suppression operation over boxes for object detection networks
 Cnvinfer1::PermutationRepresents a permutation of dimensions
 Cnvinfer1::PluginFieldStructure containing plugin attribute field names and associated data This information can be parsed to decode necessary plugin metadata
 Cnvinfer1::PluginFieldCollectionPlugin 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::safe::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::PluginTensorDescFields that a plugin might see for an input or output
 CPluginVersionDefinition of plugin versions
 Cnvinfer1::plugin::PriorBoxParametersThe PriorBox plugin layer generates the prior boxes of designated sizes and aspect ratios across all dimensions (H x W)
 Cnvinfer1::plugin::RegionParametersThe Region plugin layer performs region proposal calculation
 Cnvinfer1::plugin::RPROIParamsRPROIParams is used to create the RPROIPlugin instance
 Cnvinfer1::safe::RuntimeErrorInformationSpace to record information about runtime errors
 Cnvinfer1::plugin::softmaxTreeWhen 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::WeightsAn array of weights used as a layer parameter

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