ParserPrototxtFixture< TParser > Struct Template Reference

#include <ParserPrototxtFixture.hpp>

Collaboration diagram for ParserPrototxtFixture< TParser >:

Public Member Functions
	ParserPrototxtFixture ()
template<std::size_t NumOutputDimensions>
void	RunTest (const std::vector< float > &inputData, const std::vector< float > &expectedOutputData)
	Executes the network with the given input tensor and checks the result against the given output tensor. More...
template<std::size_t NumOutputDimensions>
void	RunComparisonTest (const std::map< std::string, std::vector< float >> &inputData, const std::map< std::string, std::vector< uint8_t >> &expectedOutputData)
	Executes the network with the given input tensor and checks the result against the given output tensor. More...
template<std::size_t NumOutputDimensions, typename T = float>
void	RunTest (const std::map< std::string, std::vector< float >> &inputData, const std::map< std::string, std::vector< T >> &expectedOutputData)
	Executes the network with the given input tensors and checks the results against the given output tensors. More...
void	SetupSingleInputSingleOutput (const std::string &inputName, const std::string &outputName)
	Parses and loads the network defined by the m_Prototext string. More...
void	SetupSingleInputSingleOutput (const armnn::TensorShape &inputTensorShape, const std::string &inputName, const std::string &outputName)
void	SetupSingleInputSingleOutput (const armnn::TensorShape &inputTensorShape, const armnn::TensorShape &outputTensorShape, const std::string &inputName, const std::string &outputName)
void	Setup (const std::map< std::string, armnn::TensorShape > &inputShapes, const std::vector< std::string > &requestedOutputs)
void	Setup (const std::map< std::string, armnn::TensorShape > &inputShapes)
void	Setup ()
armnn::IOptimizedNetworkPtr	SetupOptimizedNetwork (const std::map< std::string, armnn::TensorShape > &inputShapes, const std::vector< std::string > &requestedOutputs)

Public Attributes
std::string	m_Prototext
std::unique_ptr< TParser, void(*)(TParser *parser)>	m_Parser
armnn::IRuntimePtr	m_Runtime
armnn::NetworkId	m_NetworkIdentifier
armnn::TensorShape	m_SingleOutputShape
	This will store the output shape so it don't need to be passed to the single-input-single-output overload of RunTest(). More...
std::string	m_SingleInputName
	If the single-input-single-output overload of Setup() is called, these will store the input and output name so they don't need to be passed to the single-input-single-output overload of RunTest(). More...
std::string	m_SingleOutputName

Detailed Description

template<typename TParser>
struct armnnUtils::ParserPrototxtFixture< TParser >

Definition at line 24 of file ParserPrototxtFixture.hpp.

Constructor & Destructor Documentation

ParserPrototxtFixture()

ParserPrototxtFixture ( )

inline

Definition at line 26 of file ParserPrototxtFixture.hpp.

        : m_Parser(TParser::Create())
        , m_Runtime(armnn::IRuntime::Create(armnn::IRuntime::CreationOptions()))
        , m_NetworkIdentifier(-1)
    {
    }

Member Function Documentation

RunComparisonTest()

void RunComparisonTest	(	const std::map< std::string, std::vector< float >> &	inputData,
		const std::map< std::string, std::vector< uint8_t >> &	expectedOutputData
	)

Executes the network with the given input tensor and checks the result against the given output tensor.

Calls RunTest with output type of uint8_t for checking comparison operators.

Definition at line 194 of file ParserPrototxtFixture.hpp.

{
    RunTest<NumOutputDimensions, uint8_t>(inputData, expectedOutputData);
}

RunTest() [1/2]

void RunTest	(	const std::map< std::string, std::vector< float >> &	inputData,
		const std::map< std::string, std::vector< T >> &	expectedOutputData
	)

Executes the network with the given input tensors and checks the results against the given output tensors.

This overload supports multiple inputs and multiple outputs, identified by name.

Definition at line 203 of file ParserPrototxtFixture.hpp.

{
    // Sets up the armnn input tensors from the given vectors.
    armnn::InputTensors inputTensors;
    for (auto&& it : inputData)
    {
        armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkInputBindingInfo(it.first);
        bindingInfo.second.SetConstant(true);
        inputTensors.push_back({ bindingInfo.first, armnn::ConstTensor(bindingInfo.second, it.second.data()) });
        if (bindingInfo.second.GetNumElements() != it.second.size())
        {
            throw armnn::Exception(fmt::format("Input tensor {0} is expected to have {1} elements. "
                                               "{2} elements supplied. {3}",
                                               it.first,
                                               bindingInfo.second.GetNumElements(),
                                               it.second.size(),
                                               CHECK_LOCATION().AsString()));
        }
    }
 
    // Allocates storage for the output tensors to be written to and sets up the armnn output tensors.
    std::map<std::string, std::vector<T>> outputStorage;
    armnn::OutputTensors outputTensors;
    for (auto&& it : expectedOutputData)
    {
        armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(it.first);
        outputStorage.emplace(it.first, std::vector<T>(bindingInfo.second.GetNumElements()));
        outputTensors.push_back(
            { bindingInfo.first, armnn::Tensor(bindingInfo.second, outputStorage.at(it.first).data()) });
    }
 
    m_Runtime->EnqueueWorkload(m_NetworkIdentifier, inputTensors, outputTensors);
 
    // Compares each output tensor to the expected values.
    for (auto&& it : expectedOutputData)
    {
        armnn::BindingPointInfo bindingInfo = m_Parser->GetNetworkOutputBindingInfo(it.first);
        if (bindingInfo.second.GetNumElements() != it.second.size())
        {
            throw armnn::Exception(fmt::format("Output tensor {0} is expected to have {1} elements. "
                                               "{2} elements supplied. {3}",
                                               it.first,
                                               bindingInfo.second.GetNumElements(),
                                               it.second.size(),
                                               CHECK_LOCATION().AsString()));
        }
 
        // If the expected output shape is set, the output tensor checks will be carried out.
        if (m_SingleOutputShape.GetNumDimensions() != 0)
        {
 
            if (bindingInfo.second.GetShape().GetNumDimensions() == NumOutputDimensions &&
                bindingInfo.second.GetShape().GetNumDimensions() == m_SingleOutputShape.GetNumDimensions())
            {
                for (unsigned int i = 0; i < m_SingleOutputShape.GetNumDimensions(); ++i)
                {
                    if (m_SingleOutputShape[i] != bindingInfo.second.GetShape()[i])
                    {
                        // This exception message could not be created by fmt:format because of an oddity in
                        // the operator << of TensorShape.
                        std::stringstream message;
                        message << "Output tensor " << it.first << " is expected to have "
                                << bindingInfo.second.GetShape() << "shape. "
                                << m_SingleOutputShape << " shape supplied. "
                                << CHECK_LOCATION().AsString();
                        throw armnn::Exception(message.str());
                    }
                }
            }
            else
            {
                throw armnn::Exception(fmt::format("Output tensor {0} is expected to have {1} dimensions. "
                                                   "{2} dimensions supplied. {3}",
                                                   it.first,
                                                   bindingInfo.second.GetShape().GetNumDimensions(),
                                                   NumOutputDimensions,
                                                   CHECK_LOCATION().AsString()));
            }
        }
 
        auto outputExpected = it.second;
        auto shape = bindingInfo.second.GetShape();
        if (std::is_same<T, uint8_t>::value)
        {
            auto result = CompareTensors(outputExpected, outputStorage[it.first], shape, shape, true);
            CHECK_MESSAGE(result.m_Result, result.m_Message.str());
        }
        else
        {
            auto result = CompareTensors(outputExpected, outputStorage[it.first], shape, shape);
            CHECK_MESSAGE(result.m_Result, result.m_Message.str());
        }
    }
}

References CHECK_LOCATION.

RunTest() [2/2]

void RunTest	(	const std::vector< float > &	inputData,
		const std::vector< float > &	expectedOutputData
	)

Executes the network with the given input tensor and checks the result against the given output tensor.

This overload assumes that the network has a single input and a single output.

Definition at line 186 of file ParserPrototxtFixture.hpp.

{
    RunTest<NumOutputDimensions>({ { m_SingleInputName, inputData } }, { { m_SingleOutputName, expectedOutputData } });
}

Setup() [1/3]

void Setup

Definition at line 157 of file ParserPrototxtFixture.hpp.

{
    std::string errorMessage;
 
    armnn::INetworkPtr network =
        m_Parser->CreateNetworkFromString(m_Prototext.c_str());
    auto optimized = Optimize(*network, { armnn::Compute::CpuRef }, m_Runtime->GetDeviceSpec());
    armnn::Status ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, move(optimized), errorMessage);
    if (ret != armnn::Status::Success)
    {
        throw armnn::Exception(fmt::format("LoadNetwork failed with error: '{0}' {1}",
                                           errorMessage,
                                           CHECK_LOCATION().AsString()));
    }
}

References CHECK_LOCATION, armnn::CpuRef, armnn::Optimize(), and armnn::Success.

Setup() [2/3]

void Setup

(

const std::map< std::string, armnn::TensorShape > &

inputShapes

)

Definition at line 140 of file ParserPrototxtFixture.hpp.

{
    std::string errorMessage;
 
    armnn::INetworkPtr network =
        m_Parser->CreateNetworkFromString(m_Prototext.c_str(), inputShapes);
    auto optimized = Optimize(*network, { armnn::Compute::CpuRef }, m_Runtime->GetDeviceSpec());
    armnn::Status ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, move(optimized), errorMessage);
    if (ret != armnn::Status::Success)
    {
        throw armnn::Exception(fmt::format("LoadNetwork failed with error: '{0}' {1}",
                                           errorMessage,
                                           CHECK_LOCATION().AsString()));
    }
}

References CHECK_LOCATION, armnn::CpuRef, armnn::Optimize(), and armnn::Success.

Setup() [3/3]

void Setup	(	const std::map< std::string, armnn::TensorShape > &	inputShapes,
		const std::vector< std::string > &	requestedOutputs
	)

Definition at line 122 of file ParserPrototxtFixture.hpp.

{
    std::string errorMessage;
 
    armnn::INetworkPtr network =
        m_Parser->CreateNetworkFromString(m_Prototext.c_str(), inputShapes, requestedOutputs);
    auto optimized = Optimize(*network, { armnn::Compute::CpuRef }, m_Runtime->GetDeviceSpec());
    armnn::Status ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, move(optimized), errorMessage);
    if (ret != armnn::Status::Success)
    {
        throw armnn::Exception(fmt::format("LoadNetwork failed with error: '{0}' {1}",
                                           errorMessage,
                                           CHECK_LOCATION().AsString()));
    }
}

References CHECK_LOCATION, armnn::CpuRef, armnn::Optimize(), and armnn::Success.

SetupOptimizedNetwork()

armnn::IOptimizedNetworkPtr SetupOptimizedNetwork	(	const std::map< std::string, armnn::TensorShape > &	inputShapes,
		const std::vector< std::string > &	requestedOutputs
	)

Definition at line 174 of file ParserPrototxtFixture.hpp.

{
    armnn::INetworkPtr network =
        m_Parser->CreateNetworkFromString(m_Prototext.c_str(), inputShapes, requestedOutputs);
    auto optimized = Optimize(*network, { armnn::Compute::CpuRef }, m_Runtime->GetDeviceSpec());
    return optimized;
}

References armnn::CpuRef, and armnn::Optimize().

SetupSingleInputSingleOutput() [1/3]

void SetupSingleInputSingleOutput	(	const armnn::TensorShape &	inputTensorShape,
		const armnn::TensorShape &	outputTensorShape,
		const std::string &	inputName,
		const std::string &	outputName
	)

Definition at line 108 of file ParserPrototxtFixture.hpp.

{
    // Stores the input name, the output name and the output tensor shape
    // so they don't need to be passed to the single-input-single-output RunTest().
    m_SingleInputName = inputName;
    m_SingleOutputName = outputName;
    m_SingleOutputShape = outputTensorShape;
    Setup({ { inputName, inputTensorShape } }, { outputName });
}

SetupSingleInputSingleOutput() [2/3]

void SetupSingleInputSingleOutput	(	const armnn::TensorShape &	inputTensorShape,
		const std::string &	inputName,
		const std::string &	outputName
	)

Definition at line 97 of file ParserPrototxtFixture.hpp.

{
    // Stores the input and output name so they don't need to be passed to the single-input-single-output RunTest().
    m_SingleInputName = inputName;
    m_SingleOutputName = outputName;
    Setup({ { inputName, inputTensorShape } }, { outputName });
}

SetupSingleInputSingleOutput() [3/3]

void SetupSingleInputSingleOutput	(	const std::string &	inputName,
		const std::string &	outputName
	)

Parses and loads the network defined by the m_Prototext string.

Definition at line 87 of file ParserPrototxtFixture.hpp.

{
    // Stores the input and output name so they don't need to be passed to the single-input-single-output RunTest().
    m_SingleInputName = inputName;
    m_SingleOutputName = outputName;
    Setup({ }, { outputName });
}

Member Data Documentation

m_NetworkIdentifier

armnn::NetworkId m_NetworkIdentifier

Definition at line 72 of file ParserPrototxtFixture.hpp.

m_Parser

std::unique_ptr<TParser, void(*)(TParser* parser)> m_Parser

Definition at line 70 of file ParserPrototxtFixture.hpp.

m_Prototext

std::string m_Prototext

Definition at line 69 of file ParserPrototxtFixture.hpp.

m_Runtime

armnn::IRuntimePtr m_Runtime

Definition at line 71 of file ParserPrototxtFixture.hpp.

m_SingleInputName

std::string m_SingleInputName

If the single-input-single-output overload of Setup() is called, these will store the input and output name so they don't need to be passed to the single-input-single-output overload of RunTest().

Definition at line 77 of file ParserPrototxtFixture.hpp.

m_SingleOutputName

std::string m_SingleOutputName

Definition at line 78 of file ParserPrototxtFixture.hpp.

m_SingleOutputShape

armnn::TensorShape m_SingleOutputShape

This will store the output shape so it don't need to be passed to the single-input-single-output overload of RunTest().

Definition at line 83 of file ParserPrototxtFixture.hpp.

---

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

• src/armnnUtils/ParserPrototxtFixture.hpp