FakeQuantizationTestImpl.hpp File Reference

#include "LayerTestResult.hpp"
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>

Go to the source code of this file.

Functions
LayerTestResult< float, 2 >	FakeQuantizationTest (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)

Function Documentation

FakeQuantizationTest()

LayerTestResult<float, 2> FakeQuantizationTest	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager,
		const armnn::ITensorHandleFactory &	tensorHandleFactory
	)

Definition at line 16 of file FakeQuantizationTestImpl.cpp.

References CopyDataFromITensorHandle(), CopyDataToITensorHandle(), IWorkloadFactory::CreateFakeQuantization(), ITensorHandleFactory::CreateTensorHandle(), armnn::Float32, armnn::IgnoreUnused(), FakeQuantizationDescriptor::m_Max, FakeQuantizationDescriptor::m_Min, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, LayerTestResult< T, n >::output, and LayerTestResult< T, n >::outputExpected.

{
    IgnoreUnused(memoryManager);
    constexpr unsigned int width = 2;
    constexpr unsigned int height = 3;

    const armnn::TensorInfo tensorInfo({height, width },
        armnn::DataType::Float32);

    auto input = MakeTensor<float, 2>(tensorInfo, std::vector<float>({
       -10.0f, -5.0f,
         0.0f,  5.0f,
        10.0f, 10.0f
    }));

    LayerTestResult<float, 2> ret(tensorInfo);

    std::unique_ptr<armnn::ITensorHandle> inputHandle   = tensorHandleFactory.CreateTensorHandle(tensorInfo);
    std::unique_ptr<armnn::ITensorHandle> outputHandle  = tensorHandleFactory.CreateTensorHandle(tensorInfo);

    armnn::FakeQuantizationQueueDescriptor data;
    armnn::WorkloadInfo info;

    AddInputToWorkload(data, info, tensorInfo, inputHandle.get());
    AddOutputToWorkload(data, info, tensorInfo, outputHandle.get());

    float min = -10.f;
    float max =  10.f;

    data.m_Parameters.m_Min = min;
    data.m_Parameters.m_Max = max;

    armnn::PassthroughCpuTensorHandle refHandle(tensorInfo, &ret.outputExpected[0][0]);
    armnn::FakeQuantizationQueueDescriptor refData = data;
    armnn::WorkloadInfo refInfo = info;
    SetWorkloadOutput(refData, refInfo, 0, tensorInfo, &refHandle);

    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFakeQuantization(data, info);

    inputHandle->Allocate();
    outputHandle->Allocate();

    CopyDataToITensorHandle(inputHandle.get(), &input[0][0]);

    workload->PostAllocationConfigure();
    workload->Execute();

    CopyDataFromITensorHandle(&ret.output[0][0], outputHandle.get());

    ret.outputExpected = MakeTensor<float, 2>(tensorInfo, std::vector<float>({
        0.0f,     63.0f,
        128.0f,   191.0f,
        255.0f,   255.0f
    }));

    return ret;
}