| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonWorkloadFactoryHelper.hpp" |
| |
| |
| #include <armnnTestUtils/TensorHelpers.hpp> |
| |
| #include <armnn/backends/TensorHandle.hpp> |
| #include <armnn/backends/WorkloadFactory.hpp> |
| |
| #include <neon/NeonTimer.hpp> |
| #include <neon/NeonWorkloadFactory.hpp> |
| |
| #include <backendsCommon/test/LayerTests.hpp> |
| #include <armnnTestUtils/TensorCopyUtils.hpp> |
| #include <armnnTestUtils/WorkloadTestUtils.hpp> |
| |
| #include <doctest/doctest.h> |
| |
| #include <cstdlib> |
| #include <algorithm> |
| |
| using namespace armnn; |
| |
| TEST_SUITE("NeonTimerInstrument") |
| { |
| |
| TEST_CASE("NeonTimerGetName") |
| { |
| NeonTimer neonTimer; |
| CHECK_EQ(std::string(neonTimer.GetName()), "NeonKernelTimer"); |
| } |
| |
| TEST_CASE("NeonTimerMeasure") |
| { |
| NeonWorkloadFactory workloadFactory = |
| NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager()); |
| |
| unsigned int inputWidth = 2000u; |
| unsigned int inputHeight = 2000u; |
| unsigned int inputChannels = 1u; |
| unsigned int inputBatchSize = 1u; |
| |
| float upperBound = 1.0f; |
| float lowerBound = -1.0f; |
| |
| size_t inputSize = inputWidth * inputHeight * inputChannels * inputBatchSize; |
| std::vector<float> inputData(inputSize, 0.f); |
| std::generate(inputData.begin(), inputData.end(), [](){ |
| return (static_cast<float>(rand()) / static_cast<float>(RAND_MAX / 3)) + 1.f; }); |
| |
| unsigned int outputWidth = inputWidth; |
| unsigned int outputHeight = inputHeight; |
| unsigned int outputChannels = inputChannels; |
| unsigned int outputBatchSize = inputBatchSize; |
| |
| armnn::TensorInfo inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, |
| armnn::DataType::Float32); |
| |
| armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, |
| armnn::DataType::Float32); |
| |
| ARMNN_NO_DEPRECATE_WARN_BEGIN |
| std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| ARMNN_NO_DEPRECATE_WARN_END |
| |
| // Setup bounded ReLu |
| armnn::ActivationQueueDescriptor descriptor; |
| armnn::WorkloadInfo workloadInfo; |
| AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); |
| AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get()); |
| |
| descriptor.m_Parameters.m_Function = armnn::ActivationFunction::BoundedReLu; |
| descriptor.m_Parameters.m_A = upperBound; |
| descriptor.m_Parameters.m_B = lowerBound; |
| |
| std::unique_ptr<armnn::IWorkload> workload |
| = workloadFactory.CreateWorkload(LayerType::Activation, descriptor, workloadInfo); |
| |
| inputHandle->Allocate(); |
| outputHandle->Allocate(); |
| |
| CopyDataToITensorHandle(inputHandle.get(), inputData.data()); |
| |
| NeonTimer neonTimer; |
| // Start the timer. |
| neonTimer.Start(); |
| // Execute the workload. |
| workload->Execute(); |
| // Stop the timer. |
| neonTimer.Stop(); |
| |
| std::vector<Measurement> measurements = neonTimer.GetMeasurements(); |
| |
| CHECK(measurements.size() <= 2); |
| if (measurements.size() > 1) |
| { |
| CHECK_EQ(measurements[0].m_Name, "NeonKernelTimer/0: NEFillBorderKernel"); |
| CHECK(measurements[0].m_Value > 0.0); |
| } |
| std::ostringstream oss_neon; |
| std::ostringstream oss_cpu; |
| oss_neon << "NeonKernelTimer/" << measurements.size()-1 << ": NEActivationLayerKernel"; |
| oss_cpu << "NeonKernelTimer/" << measurements.size()-1 << ": CpuActivationKernel"; |
| bool kernelCheck = ((measurements[measurements.size()-1].m_Name.find(oss_neon.str()) != std::string::npos) |
| || (measurements[measurements.size()-1].m_Name.find(oss_cpu.str()) != std::string::npos)); |
| CHECK(kernelCheck); |
| CHECK(measurements[measurements.size()-1].m_Value > 0.0); |
| } |
| |
| } |