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Diffstat (limited to 'src/armnn/test/CreateWorkloadClNeon.hpp')
| -rw-r--r-- | src/armnn/test/CreateWorkloadClNeon.hpp | 107 |
1 files changed, 107 insertions, 0 deletions
diff --git a/src/armnn/test/CreateWorkloadClNeon.hpp b/src/armnn/test/CreateWorkloadClNeon.hpp new file mode 100644 index 0000000000..a41a70755f --- /dev/null +++ b/src/armnn/test/CreateWorkloadClNeon.hpp @@ -0,0 +1,107 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// +#pragma once + +#include "CreateWorkload.hpp" +#include "backends/RefWorkloadFactory.hpp" + +#if ARMCOMPUTECL_ENABLED +#include "backends/ClTensorHandle.hpp" +#endif + +#if ARMCOMPUTENEON_ENABLED +#include "backends/NeonTensorHandle.hpp" +#endif + + +using namespace armnn; + +namespace +{ + +using namespace std; + +template<typename IComputeTensorHandle> +boost::test_tools::predicate_result CompareTensorHandleShape(IComputeTensorHandle* tensorHandle, + std::initializer_list<unsigned int> expectedDimensions) +{ + arm_compute::ITensorInfo* info = tensorHandle->GetTensor().info(); + + auto infoNumDims = info->num_dimensions(); + auto numExpectedDims = expectedDimensions.size(); + if (infoNumDims != numExpectedDims) + { + boost::test_tools::predicate_result res(false); + res.message() << "Different number of dimensions [" << info->num_dimensions() + << "!=" << expectedDimensions.size() << "]"; + return res; + } + + size_t i = info->num_dimensions() - 1; + + for (unsigned int expectedDimension : expectedDimensions) + { + if (info->dimension(i) != expectedDimension) + { + boost::test_tools::predicate_result res(false); + res.message() << "Different dimension [" << info->dimension(i) << "!=" << expectedDimension << "]"; + return res; + } + + i--; + } + + return true; +} + +template<template <DataType> class CopyFromCpuWorkload, template <DataType> class CopyToCpuWorkload, + typename IComputeTensorHandle> +void CreateMemCopyWorkloads(IWorkloadFactory& factory) +{ + Graph graph; + RefWorkloadFactory refFactory; + + // create the layers we're testing + Layer* const layer1 = graph.AddLayer<MemCopyLayer>("layer1"); + Layer* const layer2 = graph.AddLayer<MemCopyLayer>("layer2"); + + // create extra layers + Layer* const input = graph.AddLayer<InputLayer>(0, "input"); + Layer* const output = graph.AddLayer<OutputLayer>(0, "output"); + + // connect up + TensorInfo tensorInfo({2, 3}, DataType::Float32); + Connect(input, layer1, tensorInfo); + Connect(layer1, layer2, tensorInfo); + Connect(layer2, output, tensorInfo); + + input->CreateTensorHandles(graph, refFactory); + layer1->CreateTensorHandles(graph, factory); + layer2->CreateTensorHandles(graph, refFactory); + output->CreateTensorHandles(graph, refFactory); + + // make the workloads and check them + auto workload1 = MakeAndCheckWorkload<CopyFromCpuWorkload<DataType::Float32>>(*layer1, graph, factory); + auto workload2 = MakeAndCheckWorkload<CopyToCpuWorkload<DataType::Float32>>(*layer2, graph, refFactory); + + MemCopyQueueDescriptor queueDescriptor1 = workload1->GetData(); + BOOST_TEST(queueDescriptor1.m_Inputs.size() == 1); + BOOST_TEST(queueDescriptor1.m_Outputs.size() == 1); + auto inputHandle1 = boost::polymorphic_downcast<ConstCpuTensorHandle*>(queueDescriptor1.m_Inputs[0]); + auto outputHandle1 = boost::polymorphic_downcast<IComputeTensorHandle*>(queueDescriptor1.m_Outputs[0]); + BOOST_TEST((inputHandle1->GetTensorInfo() == TensorInfo({2, 3}, DataType::Float32))); + BOOST_TEST(CompareTensorHandleShape<IComputeTensorHandle>(outputHandle1, {2, 3})); + + + MemCopyQueueDescriptor queueDescriptor2 = workload2->GetData(); + BOOST_TEST(queueDescriptor2.m_Inputs.size() == 1); + BOOST_TEST(queueDescriptor2.m_Outputs.size() == 1); + auto inputHandle2 = boost::polymorphic_downcast<IComputeTensorHandle*>(queueDescriptor2.m_Inputs[0]); + auto outputHandle2 = boost::polymorphic_downcast<CpuTensorHandle*>(queueDescriptor2.m_Outputs[0]); + BOOST_TEST(CompareTensorHandleShape<IComputeTensorHandle>(inputHandle2, {2, 3})); + BOOST_TEST((outputHandle2->GetTensorInfo() == TensorInfo({2, 3}, DataType::Float32))); +} + +}
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