// // Copyright © 2017, 2023 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include "ClWorkloadFactoryHelper.hpp" #include #include #include #include #include #include TEST_SUITE("ClOptimizedNetwork") { TEST_CASE("OptimizeValidateGpuDeviceSupportLayerNoFallback") { // build up the structure of the network armnn::INetworkPtr net(armnn::INetwork::Create()); armnn::IConnectableLayer* input = net->AddInputLayer(0); armnn::IConnectableLayer* output = net->AddOutputLayer(0); input->GetOutputSlot(0).Connect(output->GetInputSlot(0)); input->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 1, 1, 4, 4 }, armnn::DataType::Float32)); armnn::IRuntime::CreationOptions options; armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options)); std::vector backends = { armnn::Compute::GpuAcc }; armnn::IOptimizedNetworkPtr optNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec()); CHECK(optNet); // validate workloads armnn::ClWorkloadFactory fact = ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager()); const armnn::Graph& theGraph = GetGraphForTesting(optNet.get()); for (auto&& layer : theGraph) { CHECK(layer->GetBackendId() == armnn::Compute::GpuAcc); CHECK_NOTHROW( layer->CreateWorkload(fact)); } } TEST_CASE("FP16TurboModeTestOnGpuAcc") { // Test to check when Fp16 Turbo mode set // it converts the Fp32 network to Fp16 Network // add Fp32ToFp16 conversion layer after the InputLayer // add Fp16ToFp32 conversion layer after the OutputLayer // checks the other layers if they are supported in Fp16 // if they are not put the conversion layers before and after // if they are not supported in Fp16 use Fp32 instead // if there are inverse conversion layers remove them with optimization // at the moment FloorLayer is not supported in Fp16 so it rolls back to Fp32 // and inverse conversion layers are removed by the optimizer armnn::INetworkPtr net(armnn::INetwork::Create()); // Defines layers. auto input = net->AddInputLayer(0, "input layer"); // ReLu1 armnn::ActivationDescriptor activation1Descriptor; activation1Descriptor.m_Function = armnn::ActivationFunction::BoundedReLu; activation1Descriptor.m_A = 1.f; activation1Descriptor.m_B = -1.f; auto activation = net->AddActivationLayer(activation1Descriptor, "activation layer"); auto output = net->AddOutputLayer(0, "output layer"); // Connects layers. input->GetOutputSlot(0).Connect(activation->GetInputSlot(0)); activation->GetOutputSlot(0).Connect(output->GetInputSlot(0)); armnn::TensorShape shape({4}); armnn::TensorInfo info(shape, armnn::DataType::Float32); input->GetOutputSlot(0).SetTensorInfo(info); activation->GetOutputSlot(0).SetTensorInfo(info); armnn::IRuntime::CreationOptions options; armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options)); std::vector backends = {armnn::Compute::GpuAcc}; armnn::OptimizerOptionsOpaque optimizerOptions; optimizerOptions.SetReduceFp32ToFp16(true); armnn::IOptimizedNetworkPtr optimizedNet = armnn::Optimize( *net, backends, runtime->GetDeviceSpec(), optimizerOptions); const armnn::Graph& graph = GetGraphForTesting(optimizedNet.get()); // Tests that all layers are present in the graph. CHECK(graph.GetNumLayers() == 5); // Tests that the vertices exist and have correct names. CHECK(GraphHasNamedLayer(graph, "input layer")); CHECK(GraphHasNamedLayer(graph, "convert_fp32_to_fp16-0-input layer")); CHECK(GraphHasNamedLayer(graph, "activation layer")); CHECK(GraphHasNamedLayer(graph, "convert_fp16_to_fp32-0-output layer")); CHECK(GraphHasNamedLayer(graph, "output layer")); } TEST_CASE("FastMathEnabledTestOnGpuAcc") { armnn::INetworkPtr net(armnn::INetwork::Create()); armnn::IConnectableLayer* input = net->AddInputLayer(0); armnn::IConnectableLayer* output = net->AddOutputLayer(0); input->GetOutputSlot(0).Connect(output->GetInputSlot(0)); input->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 1, 1, 4, 4 }, armnn::DataType::Float32)); armnn::IRuntime::CreationOptions options; armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options)); std::vector backends = {armnn::Compute::GpuAcc}; armnn::OptimizerOptionsOpaque optimizerOptions; armnn::BackendOptions modelOptions("GpuAcc", {{"FastMathEnabled", true}}); optimizerOptions.AddModelOption(modelOptions); armnn::IOptimizedNetworkPtr optimizedNet = armnn::Optimize( *net, backends, runtime->GetDeviceSpec(), optimizerOptions); CHECK(optimizedNet); auto modelOptionsOut = GetModelOptionsForTesting(optimizedNet.get()); CHECK(modelOptionsOut.size() == 2); // FastMathEnabled and the Global to hold the import export values. CHECK(modelOptionsOut[0].GetOption(0).GetName() == "FastMathEnabled"); CHECK(modelOptionsOut[0].GetOption(0).GetValue().AsBool() == true); } TEST_CASE("CheckMLGOTuningFile") { class ClBackendContextTestClass : public armnn::ClBackendContext { public: ClBackendContextTestClass(const armnn::IRuntime::CreationOptions &options) : ClBackendContext(options) {} bool call_reload_from_file() { return m_MLGOTuner.reload_from_file(m_MLGOTuningFile); } }; const std::string validText{ "
\n" "gemm-version, [1,2,1]\n" "ip-type,gpu\n" "
\n" "\n" "0, g71 , 8, f32, best-performance, static, gemm-type, [m,n,k,n]\n" "1, g71 , 8, f32, best-performance, static, gemm-config-reshaped-only-rhs, [m,n,k,n]\n" "2, g71 , 8, f32, best-performance, static, gemm-config-reshaped, [m,n,k,n]\n" "3, g71 , 8, qasymm8, best-performance, static, gemm-type, [m,n,k,n]\n" "4, g71 , 8, qasymm8, best-performance, static, gemm-config-reshaped-only-rhs, [m,n,k,n]\n" "5, g71 , 8, qasymm8, best-performance, static, gemm-config-native, [m,n,k,n]\n" "\n" "\n" "b , 0, var, r_mn, >=, num, 2., 1, 2\n" "l , 1, gemm-type, reshaped\n" "l , 2, gemm-type, reshaped-only-rhs\n" "\n" "\n" "l ,0,gemm-config-reshaped-only-rhs, [2, 4,4,4,1,1,0]\n" "\n" "\n" "l ,0,gemm-config-reshaped,[4,2,8,16,16,1,0,1,0]\n" "\n" "\n" "l , 0, gemm-type, native\n" "\n" "\n" "l ,0,gemm-config-reshaped-only-rhs, [2, 4,4,4,1,1,0]\n" "\n" "\n" "l ,0,gemm-config-native,[4,2,8]\n" "\n"}; const std::string invalidText{"ʕノ•ᴥ•ʔノ ︵ ┻━┻"}; fs::path validFile = armnnUtils::Filesystem::NamedTempFile("validFile.mlgo"); fs::path invalidFile = armnnUtils::Filesystem::NamedTempFile("invalidFile.mlgo"); try { std::ofstream ofs1{validFile}; ofs1 << validText << std::endl; ofs1.close(); std::ofstream ofs2{invalidFile}; ofs2 << invalidText << std::endl; ofs2.close(); } catch (std::exception &e) { std::cerr << "Unable to write to file at location [" << validFile.c_str() << "] : " << e.what() << std::endl; CHECK(false); } armnn::IRuntime::CreationOptions creationOptions1; armnn::BackendOptions validOptions { "GpuAcc", { {"MLGOTuningFilePath", validFile.c_str()} } }; creationOptions1.m_BackendOptions.emplace_back(validOptions); ClBackendContextTestClass clBackendContext1(creationOptions1); CHECK(clBackendContext1.call_reload_from_file()); armnn::BackendOptions invalidOptions { "GpuAcc", { {"MLGOTuningFilePath", invalidFile.c_str()} } }; armnn::IRuntime::CreationOptions creationOptions2; creationOptions2.m_BackendOptions.emplace_back(invalidOptions); ClBackendContextTestClass clBackendContext2(creationOptions2); CHECK(clBackendContext2.call_reload_from_file() == false); armnn::BackendOptions invalidPathOptions { "GpuAcc", { {"MLGOTuningFilePath", "not_a_real_file_path"} } }; armnn::IRuntime::CreationOptions creationOptions3; creationOptions3.m_BackendOptions.emplace_back(invalidPathOptions); ClBackendContextTestClass clBackendContext3(creationOptions3); CHECK(clBackendContext3.call_reload_from_file() == false); } }