TensorRT
5.1.5.0
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The TensorRT API version 1 namespace. More...
Classes | |
class | Dims |
Structure to define the dimensions of a tensor. More... | |
class | Dims2 |
Descriptor for two-dimensional data. More... | |
class | DimsHW |
Descriptor for two-dimensional spatial data. More... | |
class | Dims3 |
Descriptor for three-dimensional data. More... | |
class | DimsCHW |
Descriptor for data with one channel dimension and two spatial dimensions. More... | |
class | Dims4 |
Descriptor for four-dimensional data. More... | |
class | DimsNCHW |
Descriptor for data with one index dimension, one channel dimension and two spatial dimensions. More... | |
class | Weights |
An array of weights used as a layer parameter. More... | |
class | IHostMemory |
Class to handle library allocated memory that is accessible to the user. More... | |
class | ITensor |
A tensor in a network definition. More... | |
class | ILayer |
Base class for all layer classes in a network definition. More... | |
class | IConvolutionLayer |
A convolution layer in a network definition. 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 | IActivationLayer |
An Activation layer in a network definition. More... | |
class | IPoolingLayer |
A Pooling layer in a network definition. More... | |
class | ILRNLayer |
A LRN layer in a network definition. More... | |
class | IScaleLayer |
A Scale layer in a network definition. More... | |
class | ISoftMaxLayer |
A Softmax layer in a network definition. More... | |
class | IConcatenationLayer |
A concatenation layer in a network definition. More... | |
class | IDeconvolutionLayer |
A deconvolution layer in a network definition. More... | |
class | IElementWiseLayer |
A elementwise layer in a network definition. More... | |
class | IGatherLayer |
class | IRNNLayer |
A RNN layer in a network definition. More... | |
class | IRNNv2Layer |
An RNN layer in a network definition, version 2. More... | |
class | IOutputDimensionsFormula |
Application-implemented interface to compute layer output sizes. More... | |
class | IPlugin |
Plugin class for user-implemented layers. More... | |
class | IPluginExt |
Plugin class for user-implemented layers. More... | |
class | IPluginV2 |
Plugin class for user-implemented layers. More... | |
class | IPluginV2Ext |
Plugin class for user-implemented layers. More... | |
class | IPluginLayer |
Layer type for plugins. More... | |
class | IPluginV2Layer |
Layer type for pluginV2. More... | |
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 | IPluginCreator |
Plugin creator class for user implemented layers. 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 | IUnaryLayer |
Layer that represents an unary operation. More... | |
class | IReduceLayer |
Layer that represents a reduction operator. More... | |
class | IPaddingLayer |
Layer that represents a padding operation. More... | |
struct | Permutation |
class | IShuffleLayer |
Layer type for shuffling data. More... | |
class | ISliceLayer |
class | ITopKLayer |
Layer that represents a TopK reduction. More... | |
class | IMatrixMultiplyLayer |
Layer that represents a Matrix Multiplication. More... | |
class | IRaggedSoftMaxLayer |
A RaggedSoftmax layer in a network definition. More... | |
class | IIdentityLayer |
A layer that represents the identity function. More... | |
class | IConstantLayer |
Layer that represents a constant value. More... | |
class | INetworkDefinition |
A network definition for input to the builder. More... | |
class | IProfiler |
Application-implemented interface for profiling. More... | |
class | IExecutionContext |
Context for executing inference using an engine. More... | |
class | ICudaEngine |
An engine for executing inference on a built network. More... | |
class | IInt8Calibrator |
Application-implemented interface for calibration. More... | |
class | IInt8EntropyCalibrator |
class | IInt8EntropyCalibrator2 |
class | IInt8LegacyCalibrator |
class | IGpuAllocator |
Application-implemented class for controlling allocation on the GPU. More... | |
class | IBuilder |
Builds an engine from a network definition. More... | |
class | IRefitter |
Updates weights in an engine. More... | |
class | IPluginFactory |
Plugin factory for deserialization. More... | |
class | IRuntime |
Allows a serialized engine to be deserialized. More... | |
class | ILogger |
Application-implemented logging interface for the builder, engine and runtime. More... | |
class | PluginRegistrar |
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. More... | |
Functions | |
template<typename T > | |
int | EnumMax () |
Maximum number of elements in an enumeration type. | |
template<> | |
int | EnumMax< DataType > () |
Maximum number of elements in DataType enum. More... | |
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int | EnumMax< DeviceType > () |
Maximum number of elements in DeviceType enum. More... | |
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int | EnumMax< DimensionType > () |
Maximum number of elements in DimensionType enum. More... | |
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int | EnumMax< LayerType > () |
Maximum number of elements in LayerType enum. More... | |
template<> | |
int | EnumMax< TensorLocation > () |
Maximum number of elements in TensorLocation enum. More... | |
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int | EnumMax< PaddingMode > () |
Maximum number of elements in PaddingMode enum. More... | |
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int | EnumMax< ActivationType > () |
Maximum number of elements in ActivationType enum. More... | |
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int | EnumMax< PoolingType > () |
Maximum number of elements in PoolingType enum. More... | |
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int | EnumMax< ScaleMode > () |
Maximum number of elements in ScaleMode enum. More... | |
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int | EnumMax< ElementWiseOperation > () |
Maximum number of elements in ElementWiseOperation enum. More... | |
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int | EnumMax< RNNOperation > () |
Maximum number of elements in RNNOperation enum. More... | |
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int | EnumMax< RNNDirection > () |
Maximum number of elements in RNNDirection enum. More... | |
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int | EnumMax< RNNInputMode > () |
Maximum number of elements in RNNInputMode enum. More... | |
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int | EnumMax< RNNGateType > () |
Maximum number of elements in RNNGateType enum. More... | |
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int | EnumMax< PluginFormat > () |
Maximum number of elements in PluginFormat enum. More... | |
template<> | |
int | EnumMax< UnaryOperation > () |
Maximum number of elements in UnaryOperation enum. More... | |
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int | EnumMax< ReduceOperation > () |
Maximum number of elements in ReduceOperation enum. More... | |
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int | EnumMax< TopKOperation > () |
Maximum number of elements in TopKOperation enum. More... | |
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int | EnumMax< MatrixOperation > () |
Maximum number of elements in MatrixOperation enum. More... | |
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int | EnumMax< CalibrationAlgoType > () |
Maximum number of elements in CalibrationAlgoType enum. More... | |
template<> | |
int | EnumMax< EngineCapability > () |
Maximum number of elements in EngineCapability enum. More... | |
template<> | |
int | EnumMax< WeightsRole > () |
Maximum number of elements in WeightsRole enum. More... | |
template<> | |
int | EnumMax< ILogger::Severity > () |
Maximum number of elements in ILogger::Severity enum. More... | |
template<> | |
int | EnumMax< PluginType > () |
The TensorRT API version 1 namespace.
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Enumerates the types of activation to perform in an activation layer.
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Version of calibration algorithm to use.
enum CalibrationAlgoType
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Enumerates the binary operations that may be performed by an ElementWise layer.
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List of supported engine capability flows.
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The type values of layer classes.
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Enumerates the operations that may be performed on a tensor by IMatrixMultiplyLayer before multiplication.
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Enumerates the modes of padding to perform in convolution, deconvolution and pooling layer, padding mode gets precedence if setPaddingMode() and setPrePadding() are also used.
kEXPLICIT* padding is to use explicit padding. kSAME* padding is to implicitly calculate padding to keep output dim to be the "same" with input dim. For convolution and pooling, output dim is ceil(input dim, stride), for deconvolution it is inverse, then use the output dim to calculate padding size. kCAFFE* padding is symmetric padding.
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Enumerator | |
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kFLOAT16 |
FP16 field type. |
kFLOAT32 |
FP32 field type. |
kFLOAT64 |
FP64 field type. |
kINT8 |
INT8 field type. |
kINT16 |
INT16 field type. |
kINT32 |
INT32 field type. |
kCHAR |
char field type. |
kDIMS |
nvinfer1::Dims field type. |
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The type values for the various plugins.
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Enumerates the RNN direction that may be performed by an RNN layer.
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kUNIDIRECTION |
Network iterations from first input to last input. |
kBIDIRECTION |
Network iterates from first to last and vice versa and outputs concatenated. |
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Identifies an individual gate within an RNN cell.
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kINPUT |
Input gate (i). |
kOUTPUT |
Output gate (o). |
kFORGET |
Forget gate (f). |
kUPDATE |
Update gate (z). |
kRESET |
Reset gate (r). |
kCELL |
Cell gate (c). |
kHIDDEN |
Hidden gate (h). |
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Enumerates the RNN input modes that may occur with an RNN layer.
If the RNN is configured with RNNInputMode::kLINEAR, then for each gate g
in the first layer of the RNN, the input vector X[t]
(length E
) is left-multiplied by the gate's corresponding weight matrix W[g]
(dimensions HxE
) as usual, before being used to compute the gate output as described by RNNOperation.
If the RNN is configured with RNNInputMode::kSKIP, then this initial matrix multiplication is "skipped" and W[g]
is conceptually an identity matrix. In this case, the input vector X[t]
must have length H
(the size of the hidden state).
Enumerator | |
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kLINEAR |
Perform the normal matrix multiplication in the first recurrent layer. |
kSKIP |
No operation is performed on the first recurrent layer. |
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Enumerates the RNN operations that may be performed by an RNN layer.
Equation definitions
In the equations below, we use the following naming convention:
Equations
Depending on the value of RNNOperation chosen, each sub-layer of the RNN layer will perform one of the following operations:
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Controls how shift, scale and power are applied in a Scale layer.
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Enumerates the unary operations that may be performed by a Unary layer.
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How a layer uses particular Weights.
The power weights of an IScaleLayer are omitted. Refitting those is not supported.
Enumerator | |
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kKERNEL |
kernel for IConvolutionLayer, IDeconvolutionLayer, or IFullyConnectedLayer |
kBIAS |
bias for IConvolutionLayer, IDeconvolutionLayer, or IFullyConnectedLayer |
kSHIFT |
shift part of IScaleLayer |
kSCALE |
scale part of IScaleLayer |
kCONSTANT |
weights for IConstantLayer |
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Maximum number of elements in ActivationType enum.
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Maximum number of elements in CalibrationAlgoType enum.
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Maximum number of elements in DataType enum.
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Maximum number of elements in DeviceType enum.
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Maximum number of elements in DimensionType enum.
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Maximum number of elements in ElementWiseOperation enum.
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Maximum number of elements in EngineCapability enum.
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Maximum number of elements in ILogger::Severity enum.
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Maximum number of elements in LayerType enum.
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Maximum number of elements in MatrixOperation enum.
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Maximum number of elements in PaddingMode enum.
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Maximum number of elements in PluginFormat enum.
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Maximum number of elements in PoolingType enum.
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Maximum number of elements in ReduceOperation enum.
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Maximum number of elements in RNNDirection enum.
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Maximum number of elements in RNNGateType enum.
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Maximum number of elements in RNNInputMode enum.
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Maximum number of elements in RNNOperation enum.
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Maximum number of elements in ScaleMode enum.
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Maximum number of elements in TensorLocation enum.
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Maximum number of elements in TopKOperation enum.
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Maximum number of elements in UnaryOperation enum.
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Maximum number of elements in WeightsRole enum.