BatchNormalizationTestImpl.hpp File Reference

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

Go to the source code of this file.

Functions
LayerTestResult< float, 4 >	BatchNormFloat32Test (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< float, 4 >	BatchNormFloat32NhwcTest (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< armnn::Half, 4 >	BatchNormFloat16Test (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< armnn::Half, 4 >	BatchNormFloat16NhwcTest (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< uint8_t, 4 >	BatchNormUint8Test (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< uint8_t, 4 >	BatchNormUint8NhwcTest (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< int16_t, 4 >	BatchNormInt16Test (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< int16_t, 4 >	BatchNormInt16NhwcTest (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)
LayerTestResult< float, 4 >	CompareBatchNormTest (armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::IWorkloadFactory &refWorkloadFactory)

Function Documentation

BatchNormFloat16NhwcTest()

LayerTestResult<armnn::Half, 4> BatchNormFloat16NhwcTest	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 349 of file BatchNormalizationTestImpl.cpp.

References armnn::NHWC.

{
    // BatchSize: 1
    // Height: 3
    // Width: 2
    // Channels: 2

    const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f,  1.f,
        4.f,  1.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f,  4.f,
        2.f,  1.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, -2.f,
        6.f,  4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f, 3.f,
        4.f, 3.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f, 4.f,
        2.f, 3.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, 2.f,
        6.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::Float16>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        0.f,
        0,
        armnn::DataLayout::NHWC);
}

BatchNormFloat16Test()

LayerTestResult<armnn::Half, 4> BatchNormFloat16Test	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 303 of file BatchNormalizationTestImpl.cpp.

References armnn::NCHW.

{
    // BatchSize: 1
    // Channels: 2
    // Height: 3
    // Width: 2

    const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
         1.f, 4.f,
         4.f, 2.f,
         1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
         1.f, 1.f,
         4.f, 1.f,
        -2.f, 4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
        1.f, 4.f,
        4.f, 2.f,
        1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
        3.f, 3.f,
        4.f, 3.f,
        2.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::Float16>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        0.f,
        0,
        armnn::DataLayout::NCHW);
}

BatchNormFloat32NhwcTest()

LayerTestResult<float, 4> BatchNormFloat32NhwcTest	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 253 of file BatchNormalizationTestImpl.cpp.

References armnn::NHWC.

{
    // BatchSize: 1
    // Height: 3
    // Width: 2
    // Channels: 2

    const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f,  1.f,
        4.f,  1.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f,  4.f,
        2.f,  1.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, -2.f,
        6.f,  4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f, 3.f,
        4.f, 3.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f, 4.f,
        2.f, 3.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, 2.f,
        6.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::Float32>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        0.f,
        0,
        armnn::DataLayout::NHWC);
}

BatchNormFloat32Test()

LayerTestResult<float, 4> BatchNormFloat32Test	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 207 of file BatchNormalizationTestImpl.cpp.

References armnn::NCHW.

{
    // BatchSize: 1
    // Channels: 2
    // Height: 3
    // Width: 2

    const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
         1.f, 4.f,
         4.f, 2.f,
         1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
         1.f, 1.f,
         4.f, 1.f,
        -2.f, 4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
        1.f, 4.f,
        4.f, 2.f,
        1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
        3.f, 3.f,
        4.f, 3.f,
        2.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::Float32>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        0.f,
        0,
        armnn::DataLayout::NCHW);
}

BatchNormInt16NhwcTest()

LayerTestResult<int16_t, 4> BatchNormInt16NhwcTest	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 537 of file BatchNormalizationTestImpl.cpp.

References armnn::NHWC.

{
    // BatchSize: 1
    // Height: 3
    // Width: 2
    // Channels: 2

    const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f,  1.f,
        4.f,  1.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f,  4.f,
        2.f,  1.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, -2.f,
        6.f,  4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f, 3.f,
        4.f, 3.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f, 4.f,
        2.f, 3.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, 2.f,
        6.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::QSymmS16>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        1.f / 20.f,
        50,
        armnn::DataLayout::NHWC);
}

BatchNormInt16Test()

LayerTestResult<int16_t, 4> BatchNormInt16Test	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 491 of file BatchNormalizationTestImpl.cpp.

References armnn::NCHW.

{
    // BatchSize: 1
    // Channels: 2
    // Height: 3
    // Width: 2

    const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
         1.f, 4.f,
         4.f, 2.f,
         1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
         1.f, 1.f,
         4.f, 1.f,
        -2.f, 4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
        1.f, 4.f,
        4.f, 2.f,
        1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
        3.f, 3.f,
        4.f, 3.f,
        2.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::QSymmS16>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        1.f / 20.f,
        50,
        armnn::DataLayout::NCHW);
}

BatchNormUint8NhwcTest()

LayerTestResult<uint8_t, 4> BatchNormUint8NhwcTest	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 445 of file BatchNormalizationTestImpl.cpp.

References armnn::NHWC.

{
    // BatchSize: 1
    // Height: 3
    // Width: 2
    // Channels: 2

    const armnn::TensorShape inputOutputShape{ 1, 3, 2, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f,  1.f,
        4.f,  1.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f,  4.f,
        2.f,  1.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, -2.f,
        6.f,  4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Height 0, Width (2) x Channel (2)
        1.f, 3.f,
        4.f, 3.f,

        // Batch 0, Height 1, Width (2) x Channel (2)
        4.f, 4.f,
        2.f, 3.f,

        // Batch 0, Height 2, Width (2) x Channel (2)
        1.f, 2.f,
        6.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::QAsymmU8>(
        workloadFactory,
        memoryManager,
        inputOutputShape, inputValues, expectedOutputValues,
         1.f/20.f, 50, armnn::DataLayout::NHWC);
}

BatchNormUint8Test()

LayerTestResult<uint8_t, 4> BatchNormUint8Test	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager
	)

Definition at line 399 of file BatchNormalizationTestImpl.cpp.

References armnn::NCHW.

{
    // BatchSize: 1
    // Channels: 2
    // Height: 3
    // Width: 2

    const armnn::TensorShape inputOutputShape{ 1, 2, 3, 2 };
    std::vector<float> inputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
         1.f, 4.f,
         4.f, 2.f,
         1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
         1.f, 1.f,
         4.f, 1.f,
        -2.f, 4.f
    };
    std::vector<float> expectedOutputValues
    {
        // Batch 0, Channel 0, Height (3) x Width (2)
        1.f, 4.f,
        4.f, 2.f,
        1.f, 6.f,

        // Batch 0, Channel 1, Height (3) x Width (2)
        3.f, 3.f,
        4.f, 3.f,
        2.f, 4.f
    };

    return BatchNormTestImpl<armnn::DataType::QAsymmU8>(
        workloadFactory,
        memoryManager,
        inputOutputShape,
        inputValues,
        expectedOutputValues,
        1.f / 20.f,
        50,
        armnn::DataLayout::NCHW);
}

CompareBatchNormTest()

LayerTestResult<float, 4> CompareBatchNormTest	(	armnn::IWorkloadFactory &	workloadFactory,
		const armnn::IBackendInternal::IMemoryManagerSharedPtr &	memoryManager,
		armnn::IWorkloadFactory &	refWorkloadFactory
	)

Definition at line 587 of file BatchNormalizationTestImpl.cpp.

References AllocateAndCopyDataToITensorHandle(), CopyDataFromITensorHandle(), CopyDataToITensorHandle(), IWorkloadFactory::CreateBatchNormalization(), IWorkloadFactory::CreateTensorHandle(), armnn::Float32, armnn::IgnoreUnused(), BatchNormalizationQueueDescriptor::m_Beta, BatchNormalizationDescriptor::m_Eps, BatchNormalizationQueueDescriptor::m_Gamma, BatchNormalizationQueueDescriptor::m_Mean, QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters, and BatchNormalizationQueueDescriptor::m_Variance.

{
    IgnoreUnused(memoryManager);
    const unsigned int width     = 2;
    const unsigned int height    = 3;
    const unsigned int channels  = 5;
    const unsigned int batchSize = 3;

    armnn::TensorInfo inputTensorInfo;
    armnn::TensorInfo outputTensorInfo;
    armnn::TensorInfo tensorInfo;

    constexpr unsigned int shape[]       = {batchSize, channels, height, width};
    constexpr unsigned int tensorShape[] = {channels};

    inputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32);
    outputTensorInfo = armnn::TensorInfo(4, shape, armnn::DataType::Float32);
    tensorInfo = armnn::TensorInfo(1, tensorShape, armnn::DataType::Float32);

    auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 21312);

    auto mean     = MakeRandomTensor<float, 1>(tensorInfo, 123);
    auto variance = MakeRandomTensor<float, 1>(tensorInfo, 234, 0.0f);
    auto beta     = MakeRandomTensor<float, 1>(tensorInfo, 123);
    auto gamma    = MakeRandomTensor<float, 1>(tensorInfo, 345);

    LayerTestResult<float,4> ret(outputTensorInfo);

    std::unique_ptr<armnn::ITensorHandle> inputHandle  = workloadFactory.CreateTensorHandle(inputTensorInfo);
    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);

    std::unique_ptr<armnn::ITensorHandle> inputHandleRef  = refWorkloadFactory.CreateTensorHandle(inputTensorInfo);
    std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.CreateTensorHandle(outputTensorInfo);

    armnn::BatchNormalizationQueueDescriptor data;
    armnn::WorkloadInfo info;
    armnn::ScopedCpuTensorHandle meanTensor(tensorInfo);
    armnn::ScopedCpuTensorHandle varianceTensor(tensorInfo);
    armnn::ScopedCpuTensorHandle betaTensor(tensorInfo);
    armnn::ScopedCpuTensorHandle gammaTensor(tensorInfo);

    AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]);
    AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]);
    AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]);
    AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]);

    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
    data.m_Mean             = &meanTensor;
    data.m_Variance         = &varianceTensor;
    data.m_Beta             = &betaTensor;
    data.m_Gamma            = &gammaTensor;
    data.m_Parameters.m_Eps = 0.01f;

    armnn::BatchNormalizationQueueDescriptor refData = data;
    armnn::WorkloadInfo refInfo = info;
    SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get());
    SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());

    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info);
    std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateBatchNormalization(refData, refInfo);

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

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

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

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

    return ret;
}