1 files changed, 105 insertions, 0 deletions
diff --git a/src/backends/neon/test/NeonTimerTest.cpp b/src/backends/neon/test/NeonTimerTest.cpp
new file mode 100644
index 0000000000..06f19c6ec3
--- /dev/null
+++ b/src/backends/neon/test/NeonTimerTest.cpp
@@ -0,0 +1,105 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <armnn/ArmNN.hpp>
+
+#include <armnn/test/TensorHelpers.hpp>
+
+#include <backends/CpuTensorHandle.hpp>
+#include <backends/WorkloadFactory.hpp>
+
+#include <backends/neon/NeonTimer.hpp>
+#include <backends/neon/NeonWorkloadFactory.hpp>
+
+#include <backends/test/LayerTests.hpp>
+#include <backends/test/TensorCopyUtils.hpp>
+#include <backends/test/WorkloadTestUtils.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+#include <cstdlib>
+#include <algorithm>
+
+using namespace armnn;
+
+BOOST_AUTO_TEST_SUITE(NeonTimerInstrument)
+
+
+BOOST_AUTO_TEST_CASE(NeonTimerGetName)
+{
+    NeonTimer neonTimer;
+    BOOST_CHECK_EQUAL(neonTimer.GetName(), "NeonKernelTimer");
+}
+
+BOOST_AUTO_TEST_CASE(NeonTimerMeasure)
+{
+    NeonWorkloadFactory workloadFactory;
+
+    unsigned int inputWidth = 4000u;
+    unsigned int inputHeight = 5000u;
+    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::GetDataType<float>());
+
+    armnn::TensorInfo outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth },
+        armnn::GetDataType<float>());
+
+    LayerTestResult<float, 4> result(inputTensorInfo);
+
+    auto input = MakeTensor<float, 4>(inputTensorInfo, inputData);
+
+    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+    // 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.CreateActivation(descriptor, workloadInfo);
+
+    inputHandle->Allocate();
+    outputHandle->Allocate();
+
+    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+
+    NeonTimer neonTimer;
+    // Start the timer.
+    neonTimer.Start();
+    // Execute the workload.
+    workload->Execute();
+    // Stop the timer.
+    neonTimer.Stop();
+
+    std::vector<Measurement> measurements = neonTimer.GetMeasurements();
+
+    BOOST_CHECK_EQUAL(measurements.size(), 2);
+    BOOST_CHECK_EQUAL(measurements[0].m_Name, "NeonKernelTimer/0: NEFillBorderKernel");
+    BOOST_CHECK(measurements[0].m_Value > 0.0);
+    BOOST_CHECK_EQUAL(measurements[1].m_Name, "NeonKernelTimer/1: NEActivationLayerKernel");
+    BOOST_CHECK(measurements[1].m_Value > 0.0);
+}
+
+BOOST_AUTO_TEST_SUITE_END()