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Diffstat (limited to 'src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp')
-rw-r--r-- | src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp | 366 |
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); -}
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