SampleOnnxMNIST Class Reference

The SampleOnnxMNIST class implements the ONNX MNIST sample. More...

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Public Member Functions
	SampleOnnxMNIST (const samplesCommon::OnnxSampleParams &params)
bool	build ()
	Function builds the network engine. More...
bool	infer ()
	Runs the TensorRT inference engine for this sample. More...

Private Types
template<typename T >
using	SampleUniquePtr = std::unique_ptr< T, samplesCommon::InferDeleter >

Private Member Functions
bool	constructNetwork (SampleUniquePtr< nvinfer1::IBuilder > &builder, SampleUniquePtr< nvinfer1::INetworkDefinition > &network, SampleUniquePtr< nvinfer1::IBuilderConfig > &config, SampleUniquePtr< nvonnxparser::IParser > &parser)
	Parses an ONNX model for MNIST and creates a TensorRT network. More...
bool	processInput (const samplesCommon::BufferManager &buffers)
	Reads the input and stores the result in a managed buffer. More...
bool	verifyOutput (const samplesCommon::BufferManager &buffers)
	Classifies digits and verify result. More...

Private Attributes
samplesCommon::OnnxSampleParams	mParams
	The parameters for the sample. More...
nvinfer1::Dims	mInputDims
	The dimensions of the input to the network. More...
nvinfer1::Dims	mOutputDims
	The dimensions of the output to the network. More...
int	mNumber {0}
	The number to classify. More...
std::shared_ptr< nvinfer1::ICudaEngine >	mEngine
	The TensorRT engine used to run the network. More...

Detailed Description

The SampleOnnxMNIST class implements the ONNX MNIST sample.

It creates the network using an ONNX model

Member Typedef Documentation

SampleUniquePtr

template<typename T >

using SampleOnnxMNIST::SampleUniquePtr = std::unique_ptr<T, samplesCommon::InferDeleter>

private

Constructor & Destructor Documentation

SampleOnnxMNIST()

SampleOnnxMNIST::SampleOnnxMNIST ( const samplesCommon::OnnxSampleParams &  params )

inline

Member Function Documentation

build()

bool SampleOnnxMNIST::build

(

)

Function builds the network engine.

Creates the network, configures the builder and creates the network engine.

This function creates the Onnx MNIST network by parsing the Onnx model and builds the engine that will be used to run MNIST (mEngine)

Returns

Returns true if the engine was created successfully and false otherwise

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infer()

bool SampleOnnxMNIST::infer

(

)

Runs the TensorRT inference engine for this sample.

This function is the main execution function of the sample. It allocates the buffer, sets inputs and executes the engine.

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constructNetwork()

bool SampleOnnxMNIST::constructNetwork ( SampleUniquePtr< nvinfer1::IBuilder > &  builder, SampleUniquePtr< nvinfer1::INetworkDefinition > &  network, SampleUniquePtr< nvinfer1::IBuilderConfig > &  config, SampleUniquePtr< nvonnxparser::IParser > &  parser  )

private

Parses an ONNX model for MNIST and creates a TensorRT network.

Uses a ONNX parser to create the Onnx MNIST Network and marks the output layers.

Parameters

network	Pointer to the network that will be populated with the Onnx MNIST network
builder	Pointer to the engine builder

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processInput()

bool SampleOnnxMNIST::processInput ( const samplesCommon::BufferManager &  buffers )

private

Reads the input and stores the result in a managed buffer.

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verifyOutput()

bool SampleOnnxMNIST::verifyOutput ( const samplesCommon::BufferManager &  buffers )

private

Classifies digits and verify result.

Returns

whether the classification output matches expectations

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Member Data Documentation

mParams

samplesCommon::OnnxSampleParams SampleOnnxMNIST::mParams

private

The parameters for the sample.

mInputDims

nvinfer1::Dims SampleOnnxMNIST::mInputDims

private

The dimensions of the input to the network.

mOutputDims

nvinfer1::Dims SampleOnnxMNIST::mOutputDims

private

The dimensions of the output to the network.

mNumber

int SampleOnnxMNIST::mNumber {0}

private

The number to classify.

mEngine

std::shared_ptr<nvinfer1::ICudaEngine> SampleOnnxMNIST::mEngine

private

The TensorRT engine used to run the network.

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The documentation for this class was generated from the following file:

• sampleOnnxMNIST.cpp