IVGCVSW-3381 Break up LayerTests.hpp into more manageable files

Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Icf39434f09fd340ad664cb3b97b8bee6d9da4838

1 files changed, 0 insertions, 366 deletions

diff --git a/src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp b/src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp
deleted file mode 100644
index 2726fdef4c..0000000000
--- a/src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp
+++ /dev/null
@@ -1,366 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#pragma once
-
-#include "TensorCopyUtils.hpp"
-#include <ResolveType.hpp>
-#include "WorkloadTestUtils.hpp"
-
-#include <armnn/Types.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
-#include <backendsCommon/IBackendInternal.hpp>
-#include <backendsCommon/WorkloadFactory.hpp>
-#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
-#include <test/TensorHelpers.hpp>
-
-namespace
-{
-
-using FloatData = std::vector<float>;
-using QuantData = std::pair<float, int32_t>;
-
-struct TestData
-{
-    static const armnn::TensorShape s_BoxEncodingsShape;
-    static const armnn::TensorShape s_ScoresShape;
-    static const armnn::TensorShape s_AnchorsShape;
-
-    static const QuantData s_BoxEncodingsQuantData;
-    static const QuantData s_ScoresQuantData;
-    static const QuantData s_AnchorsQuantData;
-
-    static const FloatData s_BoxEncodings;
-    static const FloatData s_Scores;
-    static const FloatData s_Anchors;
-};
-
-struct RegularNmsExpectedResults
-{
-    static const FloatData s_DetectionBoxes;
-    static const FloatData s_DetectionScores;
-    static const FloatData s_DetectionClasses;
-    static const FloatData s_NumDetections;
-};
-
-struct FastNmsExpectedResults
-{
-    static const FloatData s_DetectionBoxes;
-    static const FloatData s_DetectionScores;
-    static const FloatData s_DetectionClasses;
-    static const FloatData s_NumDetections;
-};
-
-const armnn::TensorShape TestData::s_BoxEncodingsShape = { 1, 6, 4 };
-const armnn::TensorShape TestData::s_ScoresShape       = { 1, 6, 3 };
-const armnn::TensorShape TestData::s_AnchorsShape      = { 6, 4 };
-
-const QuantData TestData::s_BoxEncodingsQuantData = { 1.00f, 1 };
-const QuantData TestData::s_ScoresQuantData       = { 0.01f, 0 };
-const QuantData TestData::s_AnchorsQuantData      = { 0.50f, 0 };
-
-const FloatData TestData::s_BoxEncodings =
-{
-    0.0f,  0.0f, 0.0f, 0.0f,
-    0.0f,  1.0f, 0.0f, 0.0f,
-    0.0f, -1.0f, 0.0f, 0.0f,
-    0.0f,  0.0f, 0.0f, 0.0f,
-    0.0f,  1.0f, 0.0f, 0.0f,
-    0.0f,  0.0f, 0.0f, 0.0f
-};
-
-const FloatData TestData::s_Scores =
-{
-    0.0f, 0.90f, 0.80f,
-    0.0f, 0.75f, 0.72f,
-    0.0f, 0.60f, 0.50f,
-    0.0f, 0.93f, 0.95f,
-    0.0f, 0.50f, 0.40f,
-    0.0f, 0.30f, 0.20f
-};
-
-const FloatData TestData::s_Anchors =
-{
-    0.5f,   0.5f, 1.0f, 1.0f,
-    0.5f,   0.5f, 1.0f, 1.0f,
-    0.5f,   0.5f, 1.0f, 1.0f,
-    0.5f,  10.5f, 1.0f, 1.0f,
-    0.5f,  10.5f, 1.0f, 1.0f,
-    0.5f, 100.5f, 1.0f, 1.0f
-};
-
-const FloatData RegularNmsExpectedResults::s_DetectionBoxes =
-{
-    0.0f, 10.0f, 1.0f, 11.0f,
-    0.0f, 10.0f, 1.0f, 11.0f,
-    0.0f,  0.0f, 0.0f,  0.0f
-};
-
-const FloatData RegularNmsExpectedResults::s_DetectionScores =
-{
-    0.95f, 0.93f, 0.0f
-};
-
-const FloatData RegularNmsExpectedResults::s_DetectionClasses =
-{
-    1.0f, 0.0f, 0.0f
-};
-
-const FloatData RegularNmsExpectedResults::s_NumDetections = { 2.0f };
-
-const FloatData FastNmsExpectedResults::s_DetectionBoxes =
-{
-    0.0f,  10.0f, 1.0f,  11.0f,
-    0.0f,   0.0f, 1.0f,   1.0f,
-    0.0f, 100.0f, 1.0f, 101.0f
-};
-
-const FloatData FastNmsExpectedResults::s_DetectionScores =
-{
-    0.95f, 0.9f, 0.3f
-};
-
-const FloatData FastNmsExpectedResults::s_DetectionClasses =
-{
-    1.0f, 0.0f, 0.0f
-};
-
-const FloatData FastNmsExpectedResults::s_NumDetections = { 3.0f };
-
-} // anonymous namespace
-
-template<typename FactoryType,
-         armnn::DataType ArmnnType,
-         typename T = armnn::ResolveType<ArmnnType>>
-void DetectionPostProcessImpl(const armnn::TensorInfo& boxEncodingsInfo,
-                              const armnn::TensorInfo& scoresInfo,
-                              const armnn::TensorInfo& anchorsInfo,
-                              const std::vector<T>& boxEncodingsData,
-                              const std::vector<T>& scoresData,
-                              const std::vector<T>& anchorsData,
-                              const std::vector<float>& expectedDetectionBoxes,
-                              const std::vector<float>& expectedDetectionClasses,
-                              const std::vector<float>& expectedDetectionScores,
-                              const std::vector<float>& expectedNumDetections,
-                              bool useRegularNms)
-{
-    std::unique_ptr<armnn::Profiler> profiler = std::make_unique<armnn::Profiler>();
-    armnn::ProfilerManager::GetInstance().RegisterProfiler(profiler.get());
-
-    auto memoryManager = WorkloadFactoryHelper<FactoryType>::GetMemoryManager();
-    FactoryType workloadFactory = WorkloadFactoryHelper<FactoryType>::GetFactory(memoryManager);
-
-    auto boxEncodings = MakeTensor<T, 3>(boxEncodingsInfo, boxEncodingsData);
-    auto scores = MakeTensor<T, 3>(scoresInfo, scoresData);
-    auto anchors = MakeTensor<T, 2>(anchorsInfo, anchorsData);
-
-    armnn::TensorInfo detectionBoxesInfo({ 1, 3, 4 }, armnn::DataType::Float32);
-    armnn::TensorInfo detectionScoresInfo({ 1, 3 }, armnn::DataType::Float32);
-    armnn::TensorInfo detectionClassesInfo({ 1, 3 }, armnn::DataType::Float32);
-    armnn::TensorInfo numDetectionInfo({ 1 }, armnn::DataType::Float32);
-
-    LayerTestResult<float, 3> detectionBoxesResult(detectionBoxesInfo);
-    detectionBoxesResult.outputExpected = MakeTensor<float, 3>(detectionBoxesInfo, expectedDetectionBoxes);
-    LayerTestResult<float, 2> detectionClassesResult(detectionClassesInfo);
-    detectionClassesResult.outputExpected = MakeTensor<float, 2>(detectionClassesInfo, expectedDetectionClasses);
-    LayerTestResult<float, 2> detectionScoresResult(detectionScoresInfo);
-    detectionScoresResult.outputExpected = MakeTensor<float, 2>(detectionScoresInfo, expectedDetectionScores);
-    LayerTestResult<float, 1> numDetectionsResult(numDetectionInfo);
-    numDetectionsResult.outputExpected = MakeTensor<float, 1>(numDetectionInfo, expectedNumDetections);
-
-    std::unique_ptr<armnn::ITensorHandle> boxedHandle = workloadFactory.CreateTensorHandle(boxEncodingsInfo);
-    std::unique_ptr<armnn::ITensorHandle> scoreshandle = workloadFactory.CreateTensorHandle(scoresInfo);
-    std::unique_ptr<armnn::ITensorHandle> anchorsHandle = workloadFactory.CreateTensorHandle(anchorsInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputBoxesHandle = workloadFactory.CreateTensorHandle(detectionBoxesInfo);
-    std::unique_ptr<armnn::ITensorHandle> classesHandle = workloadFactory.CreateTensorHandle(detectionClassesInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputScoresHandle = workloadFactory.CreateTensorHandle(detectionScoresInfo);
-    std::unique_ptr<armnn::ITensorHandle> numDetectionHandle = workloadFactory.CreateTensorHandle(numDetectionInfo);
-
-    armnn::ScopedCpuTensorHandle anchorsTensor(anchorsInfo);
-    AllocateAndCopyDataToITensorHandle(&anchorsTensor, &anchors[0][0]);
-
-    armnn::DetectionPostProcessQueueDescriptor data;
-    data.m_Parameters.m_UseRegularNms = useRegularNms;
-    data.m_Parameters.m_MaxDetections = 3;
-    data.m_Parameters.m_MaxClassesPerDetection = 1;
-    data.m_Parameters.m_DetectionsPerClass =1;
-    data.m_Parameters.m_NmsScoreThreshold = 0.0;
-    data.m_Parameters.m_NmsIouThreshold = 0.5;
-    data.m_Parameters.m_NumClasses = 2;
-    data.m_Parameters.m_ScaleY = 10.0;
-    data.m_Parameters.m_ScaleX = 10.0;
-    data.m_Parameters.m_ScaleH = 5.0;
-    data.m_Parameters.m_ScaleW = 5.0;
-    data.m_Anchors = &anchorsTensor;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data,  info, boxEncodingsInfo, boxedHandle.get());
-    AddInputToWorkload(data, info, scoresInfo, scoreshandle.get());
-    AddOutputToWorkload(data, info, detectionBoxesInfo, outputBoxesHandle.get());
-    AddOutputToWorkload(data, info, detectionClassesInfo, classesHandle.get());
-    AddOutputToWorkload(data, info, detectionScoresInfo, outputScoresHandle.get());
-    AddOutputToWorkload(data, info, numDetectionInfo, numDetectionHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDetectionPostProcess(data, info);
-
-    boxedHandle->Allocate();
-    scoreshandle->Allocate();
-    outputBoxesHandle->Allocate();
-    classesHandle->Allocate();
-    outputScoresHandle->Allocate();
-    numDetectionHandle->Allocate();
-
-    CopyDataToITensorHandle(boxedHandle.get(), boxEncodings.origin());
-    CopyDataToITensorHandle(scoreshandle.get(), scores.origin());
-
-    workload->Execute();
-
-    CopyDataFromITensorHandle(detectionBoxesResult.output.origin(), outputBoxesHandle.get());
-    CopyDataFromITensorHandle(detectionClassesResult.output.origin(), classesHandle.get());
-    CopyDataFromITensorHandle(detectionScoresResult.output.origin(), outputScoresHandle.get());
-    CopyDataFromITensorHandle(numDetectionsResult.output.origin(), numDetectionHandle.get());
-
-    BOOST_TEST(CompareTensors(detectionBoxesResult.output, detectionBoxesResult.outputExpected));
-    BOOST_TEST(CompareTensors(detectionClassesResult.output, detectionClassesResult.outputExpected));
-    BOOST_TEST(CompareTensors(detectionScoresResult.output, detectionScoresResult.outputExpected));
-    BOOST_TEST(CompareTensors(numDetectionsResult.output, numDetectionsResult.outputExpected));
-}
-
-template<armnn::DataType QuantizedType, typename RawType = armnn::ResolveType<QuantizedType>>
-void QuantizeData(RawType* quant, const float* dequant, const armnn::TensorInfo& info)
-{
-    for (size_t i = 0; i < info.GetNumElements(); i++)
-    {
-        quant[i] = armnn::Quantize<RawType>(
-            dequant[i], info.GetQuantizationScale(), info.GetQuantizationOffset());
-    }
-}
-
-template<typename FactoryType>
-void DetectionPostProcessRegularNmsFloatTest()
-{
-    return DetectionPostProcessImpl<FactoryType, armnn::DataType::Float32>(
-        armnn::TensorInfo(TestData::s_BoxEncodingsShape, armnn::DataType::Float32),
-        armnn::TensorInfo(TestData::s_ScoresShape, armnn::DataType::Float32),
-        armnn::TensorInfo(TestData::s_AnchorsShape, armnn::DataType::Float32),
-        TestData::s_BoxEncodings,
-        TestData::s_Scores,
-        TestData::s_Anchors,
-        RegularNmsExpectedResults::s_DetectionBoxes,
-        RegularNmsExpectedResults::s_DetectionClasses,
-        RegularNmsExpectedResults::s_DetectionScores,
-        RegularNmsExpectedResults::s_NumDetections,
-        true);
-}
-
-template<typename FactoryType,
-         armnn::DataType QuantizedType,
-         typename RawType = armnn::ResolveType<QuantizedType>>
-void DetectionPostProcessRegularNmsQuantizedTest()
-{
-    armnn::TensorInfo boxEncodingsInfo(TestData::s_BoxEncodingsShape, QuantizedType);
-    armnn::TensorInfo scoresInfo(TestData::s_ScoresShape, QuantizedType);
-    armnn::TensorInfo anchorsInfo(TestData::s_AnchorsShape, QuantizedType);
-
-    boxEncodingsInfo.SetQuantizationScale(TestData::s_BoxEncodingsQuantData.first);
-    boxEncodingsInfo.SetQuantizationOffset(TestData::s_BoxEncodingsQuantData.second);
-
-    scoresInfo.SetQuantizationScale(TestData::s_ScoresQuantData.first);
-    scoresInfo.SetQuantizationOffset(TestData::s_ScoresQuantData.second);
-
-    anchorsInfo.SetQuantizationScale(TestData::s_AnchorsQuantData.first);
-    anchorsInfo.SetQuantizationOffset(TestData::s_BoxEncodingsQuantData.second);
-
-    std::vector<RawType> boxEncodingsData(TestData::s_BoxEncodingsShape.GetNumElements());
-    QuantizeData<QuantizedType>(boxEncodingsData.data(),
-                                TestData::s_BoxEncodings.data(),
-                                boxEncodingsInfo);
-
-    std::vector<RawType> scoresData(TestData::s_ScoresShape.GetNumElements());
-    QuantizeData<QuantizedType>(scoresData.data(),
-                                TestData::s_Scores.data(),
-                                scoresInfo);
-
-    std::vector<RawType> anchorsData(TestData::s_AnchorsShape.GetNumElements());
-    QuantizeData<QuantizedType>(anchorsData.data(),
-                                TestData::s_Anchors.data(),
-                                anchorsInfo);
-
-    return DetectionPostProcessImpl<FactoryType, QuantizedType>(
-        boxEncodingsInfo,
-        scoresInfo,
-        anchorsInfo,
-        boxEncodingsData,
-        scoresData,
-        anchorsData,
-        RegularNmsExpectedResults::s_DetectionBoxes,
-        RegularNmsExpectedResults::s_DetectionClasses,
-        RegularNmsExpectedResults::s_DetectionScores,
-        RegularNmsExpectedResults::s_NumDetections,
-        true);
-}
-
-template<typename FactoryType>
-void DetectionPostProcessFastNmsFloatTest()
-{
-    return DetectionPostProcessImpl<FactoryType, armnn::DataType::Float32>(
-        armnn::TensorInfo(TestData::s_BoxEncodingsShape, armnn::DataType::Float32),
-        armnn::TensorInfo(TestData::s_ScoresShape, armnn::DataType::Float32),
-        armnn::TensorInfo(TestData::s_AnchorsShape, armnn::DataType::Float32),
-        TestData::s_BoxEncodings,
-        TestData::s_Scores,
-        TestData::s_Anchors,
-        FastNmsExpectedResults::s_DetectionBoxes,
-        FastNmsExpectedResults::s_DetectionClasses,
-        FastNmsExpectedResults::s_DetectionScores,
-        FastNmsExpectedResults::s_NumDetections,
-        false);
-}
-
-template<typename FactoryType,
-         armnn::DataType QuantizedType,
-         typename RawType = armnn::ResolveType<QuantizedType>>
-void DetectionPostProcessFastNmsQuantizedTest()
-{
-    armnn::TensorInfo boxEncodingsInfo(TestData::s_BoxEncodingsShape, QuantizedType);
-    armnn::TensorInfo scoresInfo(TestData::s_ScoresShape, QuantizedType);
-    armnn::TensorInfo anchorsInfo(TestData::s_AnchorsShape, QuantizedType);
-
-    boxEncodingsInfo.SetQuantizationScale(TestData::s_BoxEncodingsQuantData.first);
-    boxEncodingsInfo.SetQuantizationOffset(TestData::s_BoxEncodingsQuantData.second);
-
-    scoresInfo.SetQuantizationScale(TestData::s_ScoresQuantData.first);
-    scoresInfo.SetQuantizationOffset(TestData::s_ScoresQuantData.second);
-
-    anchorsInfo.SetQuantizationScale(TestData::s_AnchorsQuantData.first);
-    anchorsInfo.SetQuantizationOffset(TestData::s_BoxEncodingsQuantData.second);
-
-    std::vector<RawType> boxEncodingsData(TestData::s_BoxEncodingsShape.GetNumElements());
-    QuantizeData<QuantizedType>(boxEncodingsData.data(),
-                                TestData::s_BoxEncodings.data(),
-                                boxEncodingsInfo);
-
-    std::vector<RawType> scoresData(TestData::s_ScoresShape.GetNumElements());
-    QuantizeData<QuantizedType>(scoresData.data(),
-                                TestData::s_Scores.data(),
-                                scoresInfo);
-
-    std::vector<RawType> anchorsData(TestData::s_AnchorsShape.GetNumElements());
-    QuantizeData<QuantizedType>(anchorsData.data(),
-                                TestData::s_Anchors.data(),
-                                anchorsInfo);
-
-    return DetectionPostProcessImpl<FactoryType, QuantizedType>(
-        boxEncodingsInfo,
-        scoresInfo,
-        anchorsInfo,
-        boxEncodingsData,
-        scoresData,
-        anchorsData,
-        FastNmsExpectedResults::s_DetectionBoxes,
-        FastNmsExpectedResults::s_DetectionClasses,
-        FastNmsExpectedResults::s_DetectionScores,
-        FastNmsExpectedResults::s_NumDetections,
-        false);
-}
\ No newline at end of file