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Diffstat (limited to 'src/backends/cl/test/OpenClTimerTest.cpp')
| -rw-r--r-- | src/backends/cl/test/OpenClTimerTest.cpp | 143 |
1 files changed, 143 insertions, 0 deletions
diff --git a/src/backends/cl/test/OpenClTimerTest.cpp b/src/backends/cl/test/OpenClTimerTest.cpp new file mode 100644 index 0000000000..70ceac2a3f --- /dev/null +++ b/src/backends/cl/test/OpenClTimerTest.cpp @@ -0,0 +1,143 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#if (defined(__aarch64__)) || (defined(__x86_64__)) // disable test failing on FireFly/Armv7 + +#include <armnn/test/TensorHelpers.hpp> + +#include <backends/CpuTensorHandle.hpp> +#include <backends/WorkloadFactory.hpp> + +#include <backends/cl/ClContextControl.hpp> +#include <backends/cl/ClWorkloadFactory.hpp> +#include <backends/cl/OpenClTimer.hpp> + +#include <backends/test/TensorCopyUtils.hpp> +#include <backends/test/WorkloadTestUtils.hpp> + +#include <arm_compute/runtime/CL/CLScheduler.h> + +#include <boost/format.hpp> +#include <boost/test/unit_test.hpp> + +#include <iostream> + +using namespace armnn; + +struct OpenClFixture +{ + // Initialising ClContextControl to ensure OpenCL is loaded correctly for each test case. + // NOTE: Profiling needs to be enabled in ClContextControl to be able to obtain execution + // times from OpenClTimer. + OpenClFixture() : m_ClContextControl(nullptr, true) {} + ~OpenClFixture() {} + + ClContextControl m_ClContextControl; +}; + +BOOST_FIXTURE_TEST_SUITE(OpenClTimerBatchNorm, OpenClFixture) +using FactoryType = ClWorkloadFactory; + +BOOST_AUTO_TEST_CASE(OpenClTimerBatchNorm) +{ + ClWorkloadFactory workloadFactory; + + const unsigned int width = 2; + const unsigned int height = 3; + const unsigned int channels = 2; + const unsigned int num = 1; + int32_t qOffset = 0; + float qScale = 0.f; + + TensorInfo inputTensorInfo({num, channels, height, width}, GetDataType<float>()); + TensorInfo outputTensorInfo({num, channels, height, width}, GetDataType<float>()); + TensorInfo tensorInfo({channels}, GetDataType<float>()); + + // Set quantization parameters if the requested type is a quantized type. + if(IsQuantizedType<float>()) + { + inputTensorInfo.SetQuantizationScale(qScale); + inputTensorInfo.SetQuantizationOffset(qOffset); + outputTensorInfo.SetQuantizationScale(qScale); + outputTensorInfo.SetQuantizationOffset(qOffset); + tensorInfo.SetQuantizationScale(qScale); + tensorInfo.SetQuantizationOffset(qOffset); + } + + auto input = MakeTensor<float, 4>(inputTensorInfo, + QuantizedVector<float>(qScale, qOffset, + { + 1.f, 4.f, + 4.f, 2.f, + 1.f, 6.f, + + 1.f, 1.f, + 4.f, 1.f, + -2.f, 4.f + })); + // these values are per-channel of the input + auto mean = MakeTensor<float, 1>(tensorInfo, QuantizedVector<float>(qScale, qOffset, {3, -2})); + auto variance = MakeTensor<float, 1>(tensorInfo, QuantizedVector<float>(qScale, qOffset, {4, 9})); + auto beta = MakeTensor<float, 1>(tensorInfo, QuantizedVector<float>(qScale, qOffset, {3, 2})); + auto gamma = MakeTensor<float, 1>(tensorInfo, QuantizedVector<float>(qScale, qOffset, {2, 1})); + + std::unique_ptr<ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + BatchNormalizationQueueDescriptor data; + WorkloadInfo info; + ScopedCpuTensorHandle meanTensor(tensorInfo); + ScopedCpuTensorHandle varianceTensor(tensorInfo); + ScopedCpuTensorHandle betaTensor(tensorInfo); + ScopedCpuTensorHandle gammaTensor(tensorInfo); + + AllocateAndCopyDataToITensorHandle(&meanTensor, &mean[0]); + AllocateAndCopyDataToITensorHandle(&varianceTensor, &variance[0]); + AllocateAndCopyDataToITensorHandle(&betaTensor, &beta[0]); + AllocateAndCopyDataToITensorHandle(&gammaTensor, &gamma[0]); + + AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); + data.m_Mean = &meanTensor; + data.m_Variance = &varianceTensor; + data.m_Beta = &betaTensor; + data.m_Gamma = &gammaTensor; + data.m_Parameters.m_Eps = 0.0f; + + // for each channel: + // substract mean, divide by standard deviation (with an epsilon to avoid div by 0) + // multiply by gamma and add beta + std::unique_ptr<IWorkload> workload = workloadFactory.CreateBatchNormalization(data, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); + + OpenClTimer openClTimer; + + BOOST_CHECK_EQUAL(openClTimer.GetName(), "OpenClKernelTimer"); + + //Start the timer + openClTimer.Start(); + + //Execute the workload + workload->Execute(); + + //Stop the timer + openClTimer.Stop(); + + BOOST_CHECK_EQUAL(openClTimer.GetMeasurements().size(), 1); + + BOOST_CHECK_EQUAL(openClTimer.GetMeasurements().front().m_Name, + "OpenClKernelTimer/0: batchnormalization_layer_nchw GWS[1,3,2]"); + + BOOST_CHECK(openClTimer.GetMeasurements().front().m_Value > 0); + +} + +BOOST_AUTO_TEST_SUITE_END() + +#endif //aarch64 or x86_64
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