SampleAlgorithmSelector Class Reference

The SampleAlgorithmSelector class implements the SampleAlgorithmSelector sample. More...

Collaboration diagram for SampleAlgorithmSelector:

Public Member Functions
	SampleAlgorithmSelector (const samplesCommon::CaffeSampleParams &params)
bool	build (IAlgorithmSelector *selector)
	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 SampleAlgorithmSelector class implements the SampleAlgorithmSelector sample.

It creates the network using a trained Caffe MNIST classification model.

Member Typedef Documentation

SampleUniquePtr

template<typename T >

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

private

Constructor & Destructor Documentation

SampleAlgorithmSelector()

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

inline

Member Function Documentation

build()

bool SampleAlgorithmSelector::build

(

IAlgorithmSelector *

selector

)

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 SampleAlgorithmSelector::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 SampleAlgorithmSelector::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 SampleAlgorithmSelector::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 SampleAlgorithmSelector::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 SampleAlgorithmSelector::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> SampleAlgorithmSelector::mEngine {nullptr}

private

The TensorRT engine used to run the network.

mParams

samplesCommon::CaffeSampleParams SampleAlgorithmSelector::mParams

private

The parameters for the sample.

mInputDims

nvinfer1::Dims SampleAlgorithmSelector::mInputDims

private

The dimensions of the input to the network.

mMeanBlob

SampleUniquePtr<nvcaffeparser1::IBinaryProtoBlob> SampleAlgorithmSelector::mMeanBlob

private

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

• sampleAlgorithmSelector.cpp