diff options
Diffstat (limited to 'src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp')
| -rw-r--r-- | src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp | 160 |
1 files changed, 159 insertions, 1 deletions
diff --git a/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp b/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp index 66ccdbf1d9..16b10c88ac 100644 --- a/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp +++ b/src/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp @@ -24,6 +24,100 @@ namespace experimental template<DataType ArmnnIType, DataType ArmnnOType, typename TInput = ResolveType <ArmnnIType>, typename TOutput = ResolveType <ArmnnOType>> +void AsyncThreadedEndToEndTestImpl(INetworkPtr network, + const std::vector<std::map<int, std::vector<TInput>>>& inputTensorData, + const std::vector<std::map<int, std::vector<TOutput>>>& expectedOutputData, + std::vector<BackendId> backends, + const size_t numberOfInferences, + float tolerance = 0.000001f) +{ + // Create Runtime in which test will run + IRuntime::CreationOptions options; + IRuntimePtr runtime(IRuntime::Create(options)); + + // Optimize the Network + IOptimizedNetworkPtr optNet = Optimize(*network, backends, runtime->GetDeviceSpec()); + + + // Creates AsyncNetwork + NetworkId networkId = 0; + std::string errorMessage; + const INetworkProperties networkProperties(false, false, true); + runtime->LoadNetwork(networkId, std::move(optNet), errorMessage, networkProperties); + + std::vector<InputTensors> inputTensorsVec; + std::vector<OutputTensors> outputTensorsVec; + std::vector<std::map<int, std::vector<TOutput>>> outputStorageVec; + std::vector<std::unique_ptr<IWorkingMemHandle>> workingMemHandles; + + for (unsigned int i = 0; i < numberOfInferences; ++i) + { + InputTensors inputTensors; + OutputTensors outputTensors; + outputStorageVec.emplace_back(std::map<int, std::vector<TOutput>>()); + + inputTensors.reserve(inputTensorData.size()); + for (auto&& it : inputTensorData[i]) + { + inputTensors.push_back({it.first, + ConstTensor(runtime->GetInputTensorInfo(networkId, it.first), it.second.data())}); + } + + outputTensors.reserve(expectedOutputData.size()); + for (auto&& it : expectedOutputData[i]) + { + std::vector<TOutput> out(it.second.size()); + outputStorageVec[i].emplace(it.first, out); + outputTensors.push_back({it.first, + Tensor(runtime->GetOutputTensorInfo(networkId, it.first), + outputStorageVec[i].at(it.first).data())}); + } + + inputTensorsVec.push_back(inputTensors); + outputTensorsVec.push_back(outputTensors); + + workingMemHandles.push_back(runtime->CreateWorkingMemHandle(networkId)); + } + + std::vector<std::thread> threads; + for (unsigned int i = 0; i < numberOfInferences; ++i) + { + // Access the vectors before we do anything multi-threaded + InputTensors& inputTensors = inputTensorsVec[i]; + OutputTensors& outputTensors = outputTensorsVec[i]; + IWorkingMemHandle& workingMemHandle = *workingMemHandles[i].get(); + + threads.emplace_back([&]() + { + // Run the async network + runtime->Execute(workingMemHandle, inputTensors, outputTensors); + }); + } + + for (unsigned int i = 0; i < numberOfInferences; ++i) + { + threads[i].join(); + } + + // Checks the results. + for (unsigned int i = 0; i < numberOfInferences; ++i) + { + for (auto &&it : expectedOutputData[i]) + { + std::vector<TOutput> out = outputStorageVec[i].at(it.first); + for (unsigned int j = 0; j < out.size(); ++j) + { + BOOST_CHECK(Compare<ArmnnOType>(it.second[j], out[j], tolerance) == true); + } + } + } + +} + + + +template<DataType ArmnnIType, DataType ArmnnOType, + typename TInput = ResolveType <ArmnnIType>, typename TOutput = ResolveType <ArmnnOType>> void AsyncEndToEndTestImpl(INetworkPtr network, const std::map<int, std::vector<TInput>>& inputTensorData, const std::map<int, std::vector<TOutput>>& expectedOutputData, @@ -169,7 +263,71 @@ void StridedSlicedEndToEndTest(const std::vector<BackendId>& backends) std::map<int, std::vector<T>> inputTensorData = {{0, inputData}}; std::map<int, std::vector<T>> expectedOutputData = {{0, outputExpected}}; - AsyncEndToEndTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends); + AsyncEndToEndTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends, 1); +} + +template<armnn::DataType ArmnnType> +void StridedSlicedMultiThreadedEndToEndTest(const std::vector<BackendId>& backends) +{ + using namespace armnn; + using T = ResolveType<ArmnnType>; + + const TensorShape& inputShape = {3, 2, 3, 1}; + const TensorShape& outputShape = {1, 2, 3, 1}; + const std::vector<int>& beginData = {1, 0, 0, 0}; + const std::vector<int>& endData = {2, 2, 3, 1}; + const std::vector<int>& stridesData = {1, 1, 1, 1}; + int beginMask = 0; + int endMask = 0; + int shrinkAxisMask = 0; + int ellipsisMask = 0; + int newAxisMask = 0; + + // Builds up the structure of the network + INetworkPtr net = CreateStridedSliceNetwork<ArmnnType>(inputShape, + outputShape, + beginData, + endData, + stridesData, + beginMask, + endMask, + shrinkAxisMask, + ellipsisMask, + newAxisMask); + + BOOST_TEST_CHECKPOINT("create a network"); + + // Creates structures for input & output. + std::vector<T> inputData1{ + 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + + 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f, + + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f + }; + + std::vector<T> outputExpected1{ 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f }; + + // Creates structures for input & output. + std::vector<T> inputData2{ + 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f, + + 8.0f, 8.0f, 8.0f, 7.0f, 7.0f, 7.0f, + + 5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f + }; + + std::vector<T> outputExpected2{ 8.0f, 8.0f, 8.0f, 7.0f, 7.0f, 7.0f }; + + std::vector<std::map<int, std::vector<T>>> inputTensors; + std::vector<std::map<int, std::vector<T>>> outputTensors; + + inputTensors.push_back(std::map<int, std::vector<T>> {{0, inputData1}}); + inputTensors.push_back(std::map<int, std::vector<T>> {{0, inputData2}}); + outputTensors.push_back(std::map<int, std::vector<T>> {{0, outputExpected1}}); + outputTensors.push_back(std::map<int, std::vector<T>> {{0, outputExpected2}}); + + AsyncThreadedEndToEndTestImpl<ArmnnType, ArmnnType>(move(net), inputTensors, outputTensors, backends, 2); } } // experimental namespace |