TensorRT
|
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 | IPluginLayer |
Layer type for plugins. 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 | 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 | 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 | IInt8LegacyCalibrator |
class | IGpuAllocator |
Application-implemented class for controlling allocation on the GPU. More... | |
class | IBuilder |
Builds an engine from a network definition. 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... | |
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... | |
template<> | |
int | EnumMax< DimensionType > () |
Maximum number of elements in DimensionType enum. More... | |
template<> | |
int | EnumMax< LayerType > () |
Maximum number of elements in LayerType enum. More... | |
template<> | |
int | EnumMax< TensorLocation > () |
Maximum number of elements in TensorLocation enum. More... | |
template<> | |
int | EnumMax< ActivationType > () |
Maximum number of elements in ActivationType enum. More... | |
template<> | |
int | EnumMax< PoolingType > () |
Maximum number of elements in PoolingType enum. More... | |
template<> | |
int | EnumMax< ScaleMode > () |
Maximum number of elements in ScaleMode enum. More... | |
template<> | |
int | EnumMax< ElementWiseOperation > () |
Maximum number of elements in ElementWiseOperation enum. More... | |
template<> | |
int | EnumMax< RNNOperation > () |
Maximum number of elements in RNNOperation enum. More... | |
template<> | |
int | EnumMax< RNNDirection > () |
Maximum number of elements in RNNDirection enum. More... | |
template<> | |
int | EnumMax< RNNInputMode > () |
Maximum number of elements in RNNInputMode enum. More... | |
template<> | |
int | EnumMax< RNNGateType > () |
Maximum number of elements in RNNGateType enum. More... | |
template<> | |
int | EnumMax< PluginFormat > () |
Maximum number of elements in PluginFormat enum. More... | |
template<> | |
int | EnumMax< UnaryOperation > () |
Maximum number of elements in UnaryOperation enum. More... | |
template<> | |
int | EnumMax< ReduceOperation > () |
Maximum number of elements in ReduceOperation enum. More... | |
template<> | |
int | EnumMax< TopKOperation > () |
Maximum number of elements in TopKOperation enum. More... | |
template<> | |
int | EnumMax< CalibrationAlgoType > () |
Maximum number of elements in CalibrationAlgoType 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.
|
strong |
|
strong |
Version of calibration algorithm to use.
enum CalibrationAlgoType
|
strong |
|
strong |
|
strong |
Enumerates the binary operations that may be performed by an ElementWise layer.
|
strong |
The type values of layer classes.
|
strong |
|
strong |
The type values for the various plugins.
|
strong |
Enumerates the RNN direction that may be performed by an RNN layer.
Enumerator | |
---|---|
kUNIDIRECTION |
Network iterations from first input to last input. |
kBIDIRECTION |
Network iterates from first to last and vice versa and outputs concatenated. |
|
strong |
Identifies an individual gate within an RNN cell.
Enumerator | |
---|---|
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). |
|
strong |
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 | |
---|---|
kLINEAR |
Perform the normal matrix multiplication in the first recurrent layer. |
kSKIP |
No operation is performed on the first recurrent layer. |
|
strong |
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:
|
strong |
Controls how scale is applied in a Scale layer.
|
strong |
|
strong |
|
strong |
Enumerates the unary operations that may be performed by a Unary layer.
Enumerator | |
---|---|
kEXP |
Exponentiation. |
kLOG |
Log (base e). |
kSQRT |
Square root. |
kRECIP |
Reciprocal. |
kABS |
Absolute value. |
kNEG |
Negation. |
|
inline |
Maximum number of elements in ActivationType enum.
|
inline |
Maximum number of elements in CalibrationAlgoType enum.
|
inline |
Maximum number of elements in DataType enum.
|
inline |
Maximum number of elements in DimensionType enum.
|
inline |
Maximum number of elements in ElementWiseOperation enum.
|
inline |
Maximum number of elements in ILogger::Severity enum.
|
inline |
Maximum number of elements in LayerType enum.
|
inline |
Maximum number of elements in PluginFormat enum.
|
inline |
Maximum number of elements in PoolingType enum.
|
inline |
Maximum number of elements in ReduceOperation enum.
|
inline |
Maximum number of elements in RNNDirection enum.
|
inline |
Maximum number of elements in RNNGateType enum.
|
inline |
Maximum number of elements in RNNInputMode enum.
|
inline |
Maximum number of elements in RNNOperation enum.
|
inline |
Maximum number of elements in ScaleMode enum.
|
inline |
Maximum number of elements in TensorLocation enum.
|
inline |
Maximum number of elements in TopKOperation enum.
|
inline |
Maximum number of elements in UnaryOperation enum.