From dcaa6109c95034aa3b945acd50a2882e40f13370 Mon Sep 17 00:00:00 2001 From: Ferran Balaguer Date: Wed, 21 Aug 2019 13:28:38 +0100 Subject: IVGCVSW-3175 Add Regression Tests for Zero Copy Signed-off-by: Ferran Balaguer Change-Id: I6f16ea0dca359283a3b187e2f046f82a7dc2ff7c --- .../backendsCommon/test/EndToEndTestImpl.hpp | 153 +++++++++++++++++++++ src/backends/reference/test/RefEndToEndTests.cpp | 86 ++---------- 2 files changed, 167 insertions(+), 72 deletions(-) (limited to 'src/backends') diff --git a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp index f8673d691e..8a3e44fcca 100644 --- a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp +++ b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp @@ -8,6 +8,7 @@ #include #include +#include #include @@ -171,4 +172,156 @@ void EndToEndLayerTestImpl(INetworkPtr network, } } +inline void ImportNonAlignedPointerTest(std::vector backends) +{ + using namespace armnn; + + // Create runtime in which test will run + IRuntime::CreationOptions options; + IRuntimePtr runtime(armnn::IRuntime::Create(options)); + + // build up the structure of the network + INetworkPtr net(INetwork::Create()); + + IConnectableLayer* input = net->AddInputLayer(0); + + NormalizationDescriptor descriptor; + IConnectableLayer* norm = net->AddNormalizationLayer(descriptor); + + IConnectableLayer* output = net->AddOutputLayer(0); + + input->GetOutputSlot(0).Connect(norm->GetInputSlot(0)); + norm->GetOutputSlot(0).Connect(output->GetInputSlot(0)); + + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); + norm->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); + + // Optimize the network + IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec()); + + // Loads it into the runtime. + NetworkId netId; + runtime->LoadNetwork(netId, std::move(optNet)); + + // Creates structures for input & output + std::vector inputData + { + 1.0f, 2.0f, 3.0f, 4.0f, 5.0f + }; + + // Misaligned input + float * misalignedInputData = inputData.data(); + misalignedInputData++; + + std::vector outputData(5); + + // Misaligned output + float * misalignedOutputData = outputData.data(); + misalignedOutputData++; + + InputTensors inputTensors + { + {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), misalignedInputData)}, + }; + OutputTensors outputTensors + { + {0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), misalignedOutputData)} + }; + + // The result of the inference is not important, just the fact that there + // should not be CopyMemGeneric workloads. + runtime->GetProfiler(netId)->EnableProfiling(true); + + // Do the inference + runtime->EnqueueWorkload(netId, inputTensors, outputTensors); + + // Retrieve the Profiler.Print() output to get the workload execution + ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance(); + std::stringstream ss; + profilerManager.GetProfiler()->Print(ss);; + std::string dump = ss.str(); + + // Contains RefNormalizationWorkload + std::size_t found = dump.find("RefNormalizationWorkload"); + BOOST_TEST(found != std::string::npos); + // No Contains SyncMemGeneric (Created when importing the output tensor handle) + found = dump.find("SyncMemGeneric"); + BOOST_TEST(found == std::string::npos); + // Contains CopyMemGeneric + found = dump.find("CopyMemGeneric"); + BOOST_TEST(found != std::string::npos); +} + +inline void ImportAlignedPointerTest(std::vector backends) +{ + using namespace armnn; + + // Create runtime in which test will run + IRuntime::CreationOptions options; + IRuntimePtr runtime(armnn::IRuntime::Create(options)); + + // build up the structure of the network + INetworkPtr net(INetwork::Create()); + + IConnectableLayer* input = net->AddInputLayer(0); + + NormalizationDescriptor descriptor; + IConnectableLayer* norm = net->AddNormalizationLayer(descriptor); + + IConnectableLayer* output = net->AddOutputLayer(0); + + input->GetOutputSlot(0).Connect(norm->GetInputSlot(0)); + norm->GetOutputSlot(0).Connect(output->GetInputSlot(0)); + + input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); + norm->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); + + // Optimize the network + IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec()); + + // Loads it into the runtime. + NetworkId netId; + runtime->LoadNetwork(netId, std::move(optNet)); + + // Creates structures for input & output + std::vector inputData + { + 1.0f, 2.0f, 3.0f, 4.0f + }; + + std::vector outputData(4); + + InputTensors inputTensors + { + {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())}, + }; + OutputTensors outputTensors + { + {0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())} + }; + + // The result of the inference is not important, just the fact that there + // should not be CopyMemGeneric workloads. + runtime->GetProfiler(netId)->EnableProfiling(true); + + // Do the inference + runtime->EnqueueWorkload(netId, inputTensors, outputTensors); + + // Retrieve the Profiler.Print() output to get the workload execution + ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance(); + std::stringstream ss; + profilerManager.GetProfiler()->Print(ss);; + std::string dump = ss.str(); + + // Contains RefNormalizationWorkload + std::size_t found = dump.find("RefNormalizationWorkload"); + BOOST_TEST(found != std::string::npos); + // Contains SyncMemGeneric + found = dump.find("SyncMemGeneric"); + BOOST_TEST(found != std::string::npos); + // No contains CopyMemGeneric + found = dump.find("CopyMemGeneric"); + BOOST_TEST(found == std::string::npos); +} + } // anonymous namespace diff --git a/src/backends/reference/test/RefEndToEndTests.cpp b/src/backends/reference/test/RefEndToEndTests.cpp index 31e9b339ec..ee42c9e979 100644 --- a/src/backends/reference/test/RefEndToEndTests.cpp +++ b/src/backends/reference/test/RefEndToEndTests.cpp @@ -322,78 +322,6 @@ BOOST_AUTO_TEST_CASE(TrivialMin) BOOST_TEST(outputData[3] == 2); } -BOOST_AUTO_TEST_CASE(RefNoCopyWorkloads) -{ - using namespace armnn; - - // Create runtime in which test will run - IRuntime::CreationOptions options; - IRuntimePtr runtime(armnn::IRuntime::Create(options)); - - // build up the structure of the network - INetworkPtr net(INetwork::Create()); - - IConnectableLayer* input = net->AddInputLayer(0); - - NormalizationDescriptor descriptor; - IConnectableLayer* norm = net->AddNormalizationLayer(descriptor); - - IConnectableLayer* output = net->AddOutputLayer(0); - - input->GetOutputSlot(0).Connect(norm->GetInputSlot(0)); - norm->GetOutputSlot(0).Connect(output->GetInputSlot(0)); - - input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); - norm->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32)); - - // Optimize the network - IOptimizedNetworkPtr optNet = Optimize(*net, defaultBackends, runtime->GetDeviceSpec()); - - // Loads it into the runtime. - NetworkId netId; - runtime->LoadNetwork(netId, std::move(optNet)); - - // Creates structures for input & output - std::vector inputData - { - 1.0f, 2.0f, 3.0f, 4.0f - }; - - std::vector outputData(4); - - InputTensors inputTensors - { - {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())}, - }; - OutputTensors outputTensors - { - {0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())} - }; - - // The result of the inference is not important, just the fact that there - // should not be CopyMemGeneric workloads. - runtime->GetProfiler(netId)->EnableProfiling(true); - - // Do the inference - runtime->EnqueueWorkload(netId, inputTensors, outputTensors); - - // Retrieve the Profiler.Print() output to get the workload execution - ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance(); - std::stringstream ss; - profilerManager.GetProfiler()->Print(ss);; - std::string dump = ss.str(); - - // Contains RefNormalizationWorkload - std::size_t found = dump.find("RefNormalizationWorkload"); - BOOST_TEST(found != std::string::npos); - // Contains SyncMemGeneric - found = dump.find("SyncMemGeneric"); - BOOST_TEST(found != std::string::npos); - // No contains CopyMemGeneric - found = dump.find("CopyMemGeneric"); - BOOST_TEST(found == std::string::npos); -} - BOOST_AUTO_TEST_CASE(RefEqualSimpleEndToEndTest) { const std::vector expectedOutput({ 1, 1, 1, 1, 0, 0, 0, 0, @@ -1023,4 +951,18 @@ BOOST_AUTO_TEST_CASE(RefResizeNearestNeighborEndToEndInt16NhwcTest) ResizeNearestNeighborEndToEnd(defaultBackends, armnn::DataLayout::NHWC); } +#if !defined(__ANDROID__) +// Only run these tests on non Android platforms +BOOST_AUTO_TEST_CASE(RefImportNonAlignedPointerTest) +{ + ImportNonAlignedPointerTest(defaultBackends); +} + +BOOST_AUTO_TEST_CASE(RefImportAlignedPointerTest) +{ + ImportAlignedPointerTest(defaultBackends); +} + +#endif + BOOST_AUTO_TEST_SUITE_END() \ No newline at end of file -- cgit v1.2.1