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, 369 insertions, 0 deletions

diff --git a/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
new file mode 100644
index 0000000000..bcb5abfe72
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp
@@ -0,0 +1,369 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include <ResolveType.hpp>
+
+#include <armnn/Types.hpp>
+
+#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/IBackendInternal.hpp>
+#include <backendsCommon/WorkloadFactory.hpp>
+
+#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <backendsCommon/test/WorkloadFactoryHelper.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.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);
+}