SampleMNIST Class Reference

The SampleMNIST class implements the MNIST sample. More...

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Public Member Functions
	SampleMNIST (const samplesCommon::CaffeSampleParams &params)
bool	build ()
	Builds the network engine. More...
bool	infer ()
	Runs the TensorRT inference engine for this sample. More...
bool	teardown ()
	Used to clean up any state created in the sample class. More...

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

Private Member Functions
bool	constructNetwork (SampleUniquePtr< nvcaffeparser1::ICaffeParser > &parser, SampleUniquePtr< nvinfer1::INetworkDefinition > &network)
	uses a Caffe parser to create the MNIST Network and marks the output layers More...
bool	processInput (const samplesCommon::BufferManager &buffers, const std::string &inputTensorName, int inputFileIdx) const
	Reads the input and mean data, preprocesses, and stores the result in a managed buffer. More...
bool	verifyOutput (const samplesCommon::BufferManager &buffers, const std::string &outputTensorName, int groundTruthDigit) const
	Verifies that the output is correct and prints it. More...

Private Attributes
std::shared_ptr< nvinfer1::ICudaEngine >	mEngine {nullptr}
	The TensorRT engine used to run the network. More...
samplesCommon::CaffeSampleParams	mParams
	The parameters for the sample. More...
nvinfer1::Dims	mInputDims
	The dimensions of the input to the network. More...
SampleUniquePtr< nvcaffeparser1::IBinaryProtoBlob >	mMeanBlob

Detailed Description

The SampleMNIST class implements the MNIST sample.

It creates the network using a trained Caffe MNIST classification model

Member Typedef Documentation

SampleUniquePtr

template<typename T >

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

private

Constructor & Destructor Documentation

SampleMNIST()

SampleMNIST::SampleMNIST ( const samplesCommon::CaffeSampleParams &  params )

inline

Member Function Documentation

build()

bool SampleMNIST::build

(

)

Builds the network engine.

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

This function creates the MNIST network by parsing the caffe 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 SampleMNIST::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, executes the engine, and verifies the output.

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teardown()

bool SampleMNIST::teardown

(

)

Used to clean up any state created in the sample class.

Clean up the libprotobuf files as the parsing is complete

Note

It is not safe to use any other part of the protocol buffers library after ShutdownProtobufLibrary() has been called.

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constructNetwork()

bool SampleMNIST::constructNetwork ( SampleUniquePtr< nvcaffeparser1::ICaffeParser > &  parser, SampleUniquePtr< nvinfer1::INetworkDefinition > &  network  )

private

uses a Caffe parser to create the MNIST Network and marks the output layers

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

Parameters

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

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processInput()

bool SampleMNIST::processInput ( const samplesCommon::BufferManager &  buffers, const std::string &  inputTensorName, int  inputFileIdx  ) const

private

Reads the input and mean data, preprocesses, and stores the result in a managed buffer.

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verifyOutput()

bool SampleMNIST::verifyOutput ( const samplesCommon::BufferManager &  buffers, const std::string &  outputTensorName, int  groundTruthDigit  ) const

private

Verifies that the output is correct and prints it.

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Member Data Documentation

mEngine

std::shared_ptr<nvinfer1::ICudaEngine> SampleMNIST::mEngine {nullptr}

private

The TensorRT engine used to run the network.

mParams

samplesCommon::CaffeSampleParams SampleMNIST::mParams

private

The parameters for the sample.

mInputDims

nvinfer1::Dims SampleMNIST::mInputDims

private

The dimensions of the input to the network.

mMeanBlob

SampleUniquePtr<nvcaffeparser1::IBinaryProtoBlob> SampleMNIST::mMeanBlob

private

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

• sampleMNIST.cpp