From: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Date: Mon, 4 Feb 2019 19:05:27 +0000 (+0000)
Subject: IVGCVSW-2557 Add layer tests for Ref Detection PostProcess
X-Git-Tag: submit/tizen/20200316.035456~884
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=e0a4ad8a8e6ef271883e8029985eeab16d838972;p=platform%2Fupstream%2Farmnn.git

IVGCVSW-2557 Add layer tests for Ref Detection PostProcess

Change-Id: Ia2e512c0ed035bc6ee46cd67df5e619da9770900
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
---

diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt
index 4a1d467..124d8f2 100644
--- a/src/backends/backendsCommon/test/CMakeLists.txt
+++ b/src/backends/backendsCommon/test/CMakeLists.txt
@@ -14,6 +14,7 @@ list(APPEND armnnBackendsCommonUnitTests_sources
     ConvertFp16ToFp32TestImpl.hpp
     ConvertFp32ToFp16TestImpl.hpp
     DebugTestImpl.hpp
+    DetectionPostProcessLayerTestImpl.hpp
     DetectionPostProcessTestImpl.hpp
     EndToEndTestImpl.hpp
     FullyConnectedTestImpl.hpp
diff --git a/src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp b/src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp
new file mode 100644
index 0000000..2a2c1f9
--- /dev/null
+++ b/src/backends/backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp
@@ -0,0 +1,363 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "TensorCopyUtils.hpp"
+#include "TypeUtils.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>
+
+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));
+}
+
+inline void QuantizeData(uint8_t* quant, const float* dequant, const armnn::TensorInfo& info)
+{
+    for (size_t i = 0; i < info.GetNumElements(); i++)
+    {
+        quant[i] = armnn::Quantize<uint8_t>(dequant[i], info.GetQuantizationScale(), info.GetQuantizationOffset());
+    }
+}
+
+template <typename FactoryType>
+void DetectionPostProcessRegularNmsFloatTest()
+{
+    armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, armnn::DataType::Float32);
+    armnn::TensorInfo scoresInfo({ 1, 6, 3}, armnn::DataType::Float32);
+    armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32);
+
+    std::vector<float> boxEncodingsData({
+        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
+    });
+    std::vector<float> scoresData({
+        0.0f, 0.9f, 0.8f,
+        0.0f, 0.75f, 0.72f,
+        0.0f, 0.6f, 0.5f,
+        0.0f, 0.93f, 0.95f,
+        0.0f, 0.5f, 0.4f,
+        0.0f, 0.3f, 0.2f
+    });
+    std::vector<float> anchorsData({
+        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
+    });
+
+    std::vector<float> expectedDetectionBoxes({
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 0.0f, 0.0f, 0.0f
+    });
+    std::vector<float> expectedDetectionScores({ 0.95f, 0.93f, 0.0f });
+    std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
+    std::vector<float> expectedNumDetections({ 2.0f });
+
+    return DetectionPostProcessImpl<FactoryType, armnn::DataType::Float32>(boxEncodingsInfo,
+                                                                           scoresInfo,
+                                                                           anchorsInfo,
+                                                                           boxEncodingsData,
+                                                                           scoresData,
+                                                                           anchorsData,
+                                                                           expectedDetectionBoxes,
+                                                                           expectedDetectionClasses,
+                                                                           expectedDetectionScores,
+                                                                           expectedNumDetections,
+                                                                           true);
+}
+
+template <typename FactoryType>
+void DetectionPostProcessRegularNmsUint8Test()
+{
+    armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, armnn::DataType::QuantisedAsymm8);
+    armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::QuantisedAsymm8);
+    armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::QuantisedAsymm8);
+
+    boxEncodingsInfo.SetQuantizationScale(1.0f);
+    boxEncodingsInfo.SetQuantizationOffset(1);
+    scoresInfo.SetQuantizationScale(0.01f);
+    scoresInfo.SetQuantizationOffset(0);
+    anchorsInfo.SetQuantizationScale(0.5f);
+    anchorsInfo.SetQuantizationOffset(0);
+
+    std::vector<float> 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
+    });
+    std::vector<float> scores({
+        0.0f, 0.9f, 0.8f,
+        0.0f, 0.75f, 0.72f,
+        0.0f, 0.6f, 0.5f,
+        0.0f, 0.93f, 0.95f,
+        0.0f, 0.5f, 0.4f,
+        0.0f, 0.3f, 0.2f
+    });
+    std::vector<float> 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
+    });
+
+    std::vector<uint8_t> boxEncodingsData(boxEncodings.size(), 0);
+    std::vector<uint8_t> scoresData(scores.size(), 0);
+    std::vector<uint8_t> anchorsData(anchors.size(), 0);
+    QuantizeData(boxEncodingsData.data(), boxEncodings.data(), boxEncodingsInfo);
+    QuantizeData(scoresData.data(), scores.data(), scoresInfo);
+    QuantizeData(anchorsData.data(), anchors.data(), anchorsInfo);
+
+    std::vector<float> expectedDetectionBoxes({
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 0.0f, 0.0f, 0.0f
+    });
+    std::vector<float> expectedDetectionScores({ 0.95f, 0.93f, 0.0f });
+    std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
+    std::vector<float> expectedNumDetections({ 2.0f });
+
+    return DetectionPostProcessImpl<FactoryType, armnn::DataType::QuantisedAsymm8>(boxEncodingsInfo,
+                                                                                   scoresInfo,
+                                                                                   anchorsInfo,
+                                                                                   boxEncodingsData,
+                                                                                   scoresData,
+                                                                                   anchorsData,
+                                                                                   expectedDetectionBoxes,
+                                                                                   expectedDetectionClasses,
+                                                                                   expectedDetectionScores,
+                                                                                   expectedNumDetections,
+                                                                                   true);
+}
+
+template <typename FactoryType>
+void DetectionPostProcessFastNmsFloatTest()
+{
+    armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, armnn::DataType::Float32);
+    armnn::TensorInfo scoresInfo({ 1, 6, 3}, armnn::DataType::Float32);
+    armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32);
+
+    std::vector<float> boxEncodingsData({
+        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
+    });
+    std::vector<float> scoresData({
+        0.0f, 0.9f, 0.8f,
+        0.0f, 0.75f, 0.72f,
+        0.0f, 0.6f, 0.5f,
+        0.0f, 0.93f, 0.95f,
+        0.0f, 0.5f, 0.4f,
+        0.0f, 0.3f, 0.2f
+    });
+    std::vector<float> anchorsData({
+        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
+    });
+
+    std::vector<float> expectedDetectionBoxes({
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 0.0f, 1.0f, 1.0f,
+        0.0f, 100.0f, 1.0f, 101.0f
+    });
+    std::vector<float> expectedDetectionScores({ 0.95f, 0.9f, 0.3f });
+    std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
+    std::vector<float> expectedNumDetections({ 3.0f });
+
+    return DetectionPostProcessImpl<FactoryType, armnn::DataType::Float32>(boxEncodingsInfo,
+                                                                           scoresInfo,
+                                                                           anchorsInfo,
+                                                                           boxEncodingsData,
+                                                                           scoresData,
+                                                                           anchorsData,
+                                                                           expectedDetectionBoxes,
+                                                                           expectedDetectionClasses,
+                                                                           expectedDetectionScores,
+                                                                           expectedNumDetections,
+                                                                           false);
+}
+
+template <typename FactoryType>
+void DetectionPostProcessFastNmsUint8Test()
+{
+    armnn::TensorInfo boxEncodingsInfo({ 1, 6, 4 }, armnn::DataType::QuantisedAsymm8);
+    armnn::TensorInfo scoresInfo({ 1, 6, 3 }, armnn::DataType::QuantisedAsymm8);
+    armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::QuantisedAsymm8);
+
+    boxEncodingsInfo.SetQuantizationScale(1.0f);
+    boxEncodingsInfo.SetQuantizationOffset(1);
+    scoresInfo.SetQuantizationScale(0.01f);
+    scoresInfo.SetQuantizationOffset(0);
+    anchorsInfo.SetQuantizationScale(0.5f);
+    anchorsInfo.SetQuantizationOffset(0);
+
+    std::vector<float> 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
+    });
+    std::vector<float> scores({
+        0.0f, 0.9f, 0.8f,
+        0.0f, 0.75f, 0.72f,
+        0.0f, 0.6f, 0.5f,
+        0.0f, 0.93f, 0.95f,
+        0.0f, 0.5f, 0.4f,
+        0.0f, 0.3f, 0.2f
+    });
+    std::vector<float> 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
+    });
+
+    std::vector<uint8_t> boxEncodingsData(boxEncodings.size(), 0);
+    std::vector<uint8_t> scoresData(scores.size(), 0);
+    std::vector<uint8_t> anchorsData(anchors.size(), 0);
+    QuantizeData(boxEncodingsData.data(), boxEncodings.data(), boxEncodingsInfo);
+    QuantizeData(scoresData.data(), scores.data(), scoresInfo);
+    QuantizeData(anchorsData.data(), anchors.data(), anchorsInfo);
+
+    std::vector<float> expectedDetectionBoxes({
+        0.0f, 10.0f, 1.0f, 11.0f,
+        0.0f, 0.0f, 1.0f, 1.0f,
+        0.0f, 100.0f, 1.0f, 101.0f
+    });
+    std::vector<float> expectedDetectionScores({ 0.95f, 0.9f, 0.3f });
+    std::vector<float> expectedDetectionClasses({ 1.0f, 0.0f, 0.0f });
+    std::vector<float> expectedNumDetections({ 3.0f });
+
+    return DetectionPostProcessImpl<FactoryType, armnn::DataType::QuantisedAsymm8>(boxEncodingsInfo,
+                                                                                   scoresInfo,
+                                                                                   anchorsInfo,
+                                                                                   boxEncodingsData,
+                                                                                   scoresData,
+                                                                                   anchorsData,
+                                                                                   expectedDetectionBoxes,
+                                                                                   expectedDetectionClasses,
+                                                                                   expectedDetectionScores,
+                                                                                   expectedNumDetections,
+                                                                                   false);
+}
diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp
index cfe02e6..b4ef85a 100644
--- a/src/backends/reference/test/RefLayerTests.cpp
+++ b/src/backends/reference/test/RefLayerTests.cpp
@@ -9,6 +9,7 @@
 #include <test/UnitTests.hpp>
 
 #include <reference/RefWorkloadFactory.hpp>
+#include <backendsCommon/test/DetectionPostProcessLayerTestImpl.hpp>
 #include <backendsCommon/test/LayerTests.hpp>
 
 #include <boost/test/unit_test.hpp>
@@ -500,4 +501,23 @@ ARMNN_AUTO_TEST_CASE(GatherMultiDimParamsUint8, GatherMultiDimParamsUint8Test)
 ARMNN_AUTO_TEST_CASE(GatherMultiDimParamsMultiDimIndicesFloat, GatherMultiDimParamsMultiDimIndicesFloatTest)
 ARMNN_AUTO_TEST_CASE(GatherMultiDimParamsMultiDimIndicesUint8, GatherMultiDimParamsMultiDimIndicesUint8Test)
 
+// Detection PostProcess
+BOOST_AUTO_TEST_CASE(DetectionPostProcessRegularNmsFloat)
+{
+    DetectionPostProcessRegularNmsFloatTest<armnn::RefWorkloadFactory>();
+}
+BOOST_AUTO_TEST_CASE(DetectionPostProcessFastNmsFloat)
+{
+    DetectionPostProcessFastNmsFloatTest<armnn::RefWorkloadFactory>();
+}
+BOOST_AUTO_TEST_CASE(DetectionPostProcessRegularNmsUint8)
+{
+    DetectionPostProcessRegularNmsUint8Test<armnn::RefWorkloadFactory>();
+}
+BOOST_AUTO_TEST_CASE(DetectionPostProcessFastNmsUint8)
+{
+    DetectionPostProcessFastNmsUint8Test<armnn::RefWorkloadFactory>();
+}
+
+
 BOOST_AUTO_TEST_SUITE_END()