SampleMNISTAPI Class Reference

The SampleMNISTAPI class implements the MNIST API sample. More...

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Public Member Functions
	SampleMNISTAPI (const SampleMNISTAPIParams &params)
bool	build ()
	Function builds the network engine. More...
bool	infer ()
	Runs the TensorRT inference engine for this sample. More...
bool	teardown ()
	Cleans 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< nvinfer1::IBuilder > &builder, SampleUniquePtr< nvinfer1::INetworkDefinition > &network, SampleUniquePtr< nvinfer1::IBuilderConfig > &config)
	Uses the API to create the MNIST 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...
std::map< std::string, nvinfer1::Weights >	loadWeights (const std::string &file)
	Loads weights from weights file. More...

Private Attributes
SampleMNISTAPIParams	mParams
	The parameters for the sample. More...
int	mNumber {0}
	The number to classify. More...
std::map< std::string, nvinfer1::Weights >	mWeightMap
	The weight name to weight value map. More...
std::vector< SampleUniquePtr< nvinfer1::IHostMemory > >	weightsMemory
	Host weights memory holder. More...
std::shared_ptr< nvinfer1::ICudaEngine >	mEngine
	The TensorRT engine used to run the network. More...

Detailed Description

The SampleMNISTAPI class implements the MNIST API sample.

It creates the network for MNIST classification using the API

Member Typedef Documentation

SampleUniquePtr

template<typename T >

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

private

Constructor & Destructor Documentation

SampleMNISTAPI()

SampleMNISTAPI::SampleMNISTAPI ( const SampleMNISTAPIParams &  params )

inline

Member Function Documentation

build()

bool SampleMNISTAPI::build

(

)

Function builds the network engine.

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

This function creates the MNIST network by using the API to create a 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 SampleMNISTAPI::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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teardown()

bool SampleMNISTAPI::teardown

(

)

Cleans up any state created in the sample class.

constructNetwork()

bool SampleMNISTAPI::constructNetwork ( SampleUniquePtr< nvinfer1::IBuilder > &  builder, SampleUniquePtr< nvinfer1::INetworkDefinition > &  network, SampleUniquePtr< nvinfer1::IBuilderConfig > &  config  )

private

Uses the API to create the MNIST Network.

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 SampleMNISTAPI::processInput ( const samplesCommon::BufferManager &  buffers )

private

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

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verifyOutput()

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

private

Classifies digits and verify result.

Returns

whether the classification output matches expectations

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loadWeights()

std::map< std::string, nvinfer1::Weights > SampleMNISTAPI::loadWeights ( const std::string &  file )

private

Loads weights from weights file.

TensorRT weight files have a simple space delimited format [type] [size] <data x size in hex>

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Member Data Documentation

mParams

SampleMNISTAPIParams SampleMNISTAPI::mParams

private

The parameters for the sample.

mNumber

int SampleMNISTAPI::mNumber {0}

private

The number to classify.

mWeightMap

std::map<std::string, nvinfer1::Weights> SampleMNISTAPI::mWeightMap

private

The weight name to weight value map.

weightsMemory

std::vector<SampleUniquePtr<nvinfer1::IHostMemory> > SampleMNISTAPI::weightsMemory

private

Host weights memory holder.

mEngine

std::shared_ptr<nvinfer1::ICudaEngine> SampleMNISTAPI::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:

• sampleMNISTAPI.cpp