| // |
| // Copyright © 2020 Samsung Electronics Co Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "ReduceSumTestImpl.hpp" |
| |
| #include <DataTypeUtils.hpp> |
| #include <armnnTestUtils/TensorCopyUtils.hpp> |
| #include <armnnTestUtils/WorkloadTestUtils.hpp> |
| |
| #include <armnnTestUtils/TensorHelpers.hpp> |
| |
| namespace |
| { |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<float, 4> ReduceTestCommon( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory, |
| const armnn::TensorInfo inputTensorInfo, |
| const armnn::TensorInfo outputTensorInfo, |
| const std::vector<float>& inputData, |
| const std::vector<float>& outputData, |
| const std::vector<int32_t> vAxis, |
| const armnn::ReduceOperation reduceOperation, |
| bool keepDims = false) |
| { |
| IgnoreUnused(memoryManager); |
| auto inputTensor = ConvertToDataType<ArmnnType>(inputData, inputTensorInfo); |
| |
| std::vector<float> actualOutput(outputTensorInfo.GetNumElements()); |
| |
| std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| |
| armnn::ReduceQueueDescriptor descriptor; |
| std::vector<uint32_t> updated_idx; |
| uint32_t resolvedAxis = 0; |
| for (uint32_t i = 0; i < vAxis.size(); ++i) |
| { |
| if (vAxis[i] < 0) |
| { |
| resolvedAxis = inputTensorInfo.GetNumDimensions() + static_cast<uint32_t>(vAxis[i]); |
| } else |
| { |
| resolvedAxis = static_cast<uint32_t>(vAxis[i]); |
| } |
| |
| updated_idx.push_back(resolvedAxis); |
| } |
| |
| descriptor.m_Parameters.m_vAxis = updated_idx; |
| descriptor.m_Parameters.m_ReduceOperation = reduceOperation; |
| descriptor.m_Parameters.m_KeepDims = keepDims; |
| armnn::WorkloadInfo info; |
| |
| AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| |
| std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::Reduce, |
| descriptor, |
| info); |
| |
| inputHandle->Allocate(); |
| outputHandle->Allocate(); |
| |
| CopyDataToITensorHandle(inputHandle.get(), inputTensor.data()); |
| |
| workload->Execute(); |
| |
| CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| |
| return LayerTestResult<float, 4>(actualOutput, |
| outputData, |
| outputHandle->GetShape(), |
| outputTensorInfo.GetShape()); |
| } |
| |
| } // namespace |
| |
| template<armnn::DataType ArmnnType, typename T> |
| LayerTestResult<float, 4> ReduceSumSimpleTest( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const armnn::TensorShape inputShape{ 1, 1, 1, 5 }; |
| const armnn::TensorShape outputShape{ 1, 1, 1, 1}; |
| |
| armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| |
| if (armnn::IsQuantizedType<T>()) |
| { |
| inputTensorInfo.SetQuantizationScale(1.0f); |
| inputTensorInfo.SetQuantizationOffset(0); |
| } |
| |
| armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| |
| std::vector<float> inputValues({ 5.0f, 2.0f, 8.0f, 10.0f, 9.0f }); |
| std::vector<float> outputValues({ 34.0f }); |
| |
| return ReduceTestCommon<ArmnnType>(workloadFactory, |
| memoryManager, |
| tensorHandleFactory, |
| inputTensorInfo, |
| outputTensorInfo, |
| inputValues, |
| outputValues, |
| { -1 }, |
| armnn::ReduceOperation::Sum); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T> |
| LayerTestResult<float, 4> ReduceSumSingleAxisTest1( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const armnn::TensorShape inputShape{ 1, 3, 2, 4 }; |
| const armnn::TensorShape outputShape{ 1, 1, 2, 4}; |
| |
| armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| |
| if (armnn::IsQuantizedType<T>()) |
| { |
| inputTensorInfo.SetQuantizationScale(1.0f); |
| inputTensorInfo.SetQuantizationOffset(0); |
| } |
| |
| armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| |
| std::vector<float> inputValues({ 1.0f, 2.0f, 3.0f, 4.0f, |
| 5.0f, 6.0f, 7.0f, 8.0f, |
| |
| 10.0f, 20.0f, 30.0f, 40.0f, |
| 50.0f, 60.0f, 70.0f, 80.0f, |
| |
| 100.0f, 200.0f, 300.0f, 400.0f, |
| 500.0f, 600.0f, 700.0f, 800.0f }); |
| std::vector<float> outputValues({ 111.0f, 222.0f, 333.0f, 444.0f, |
| 555.0f, 666.0f, 777.0f, 888.0f }); |
| |
| return ReduceTestCommon<ArmnnType>(workloadFactory, |
| memoryManager, |
| tensorHandleFactory, |
| inputTensorInfo, |
| outputTensorInfo, |
| inputValues, |
| outputValues, |
| { 1 }, |
| armnn::ReduceOperation::Sum); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T> |
| LayerTestResult<float, 4> ReduceSumSingleAxisTest2( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const armnn::TensorShape inputShape{ 1, 6, 3, 4 }; |
| const armnn::TensorShape outputShape{ 1, 1, 3, 4}; |
| |
| armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| |
| if (armnn::IsQuantizedType<T>()) |
| { |
| inputTensorInfo.SetQuantizationScale(1.0f); |
| inputTensorInfo.SetQuantizationOffset(0); |
| } |
| |
| armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| |
| std::vector<float> inputValues( {7, 8, 6, 1, |
| 1, 1, 8, 7, |
| 3, 7, 7, 7, |
| |
| 6, 8, 4, 7, |
| 3, 8, 7, 3, |
| 5, 8, 8, 8, |
| |
| |
| 7, 8, 2, 7, |
| 3, 8, 5, 6, |
| 8, 4, 2, 7, |
| |
| 1, 6, 7, 2, |
| 8, 3, 3, 1, |
| 7, 6, 2, 6, |
| |
| |
| 5, 3, 4, 8, |
| 7, 8, 2, 4, |
| 6, 6, 2, 8, |
| |
| 2, 2, 7, 2, |
| 5, 3, 6, 3, |
| 6, 1, 8, 8}); |
| std::vector<float> outputValues({ 28.0f, 35.0f, 30.0f, 27.0f, |
| 27.0f, 31.0f, 31.0f, 24.0f, |
| 35.0f, 32.0f, 29.0f, 44.0f}); |
| |
| return ReduceTestCommon<ArmnnType>(workloadFactory, |
| memoryManager, |
| tensorHandleFactory, |
| inputTensorInfo, |
| outputTensorInfo, |
| inputValues, |
| outputValues, |
| { 1 }, |
| armnn::ReduceOperation::Sum); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T> |
| LayerTestResult<float, 4> ReduceSumSingleAxisTest3( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const armnn::TensorShape inputShape{ 1, 6, 3, 4 }; |
| const armnn::TensorShape outputShape{ 1, 6, 3, 1}; |
| |
| armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| |
| if (armnn::IsQuantizedType<T>()) |
| { |
| inputTensorInfo.SetQuantizationScale(1.0f); |
| inputTensorInfo.SetQuantizationOffset(0); |
| } |
| |
| armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| |
| std::vector<float> inputValues( {7, 8, 6, 1, |
| 1, 1, 8, 7, |
| 3, 7, 7, 7, |
| |
| 6, 8, 4, 7, |
| 3, 8, 7, 3, |
| 5, 8, 8, 8, |
| |
| |
| 7, 8, 2, 7, |
| 3, 8, 5, 6, |
| 8, 4, 2, 7, |
| |
| 1, 6, 7, 2, |
| 8, 3, 3, 1, |
| 7, 6, 2, 6, |
| |
| |
| 5, 3, 4, 8, |
| 7, 8, 2, 4, |
| 6, 6, 2, 8, |
| |
| 2, 2, 7, 2, |
| 5, 3, 6, 3, |
| 6, 1, 8, 8}); |
| std::vector<float> outputValues({ 22.0f, 17.0f, 24.0f, |
| 25.0f, 21.0f, 29.0f, |
| |
| 24.0f, 22.0f, 21.0f, |
| 16.0f, 15.0f, 21.0f, |
| |
| 20.0f, 21.0f, 22.0f, |
| 13.0f, 17.0f, 23.0f}); |
| |
| return ReduceTestCommon<ArmnnType>(workloadFactory, |
| memoryManager, |
| tensorHandleFactory, |
| inputTensorInfo, |
| outputTensorInfo, |
| inputValues, |
| outputValues, |
| { 3 }, |
| armnn::ReduceOperation::Sum, |
| true); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T> |
| LayerTestResult<float, 4> ReduceSumMultipleAxisTest( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const armnn::TensorShape inputShape{ 1, 3, 2, 4 }; |
| const armnn::TensorShape outputShape{ 1, 1, 1, 4}; |
| |
| armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); |
| |
| if (armnn::IsQuantizedType<T>()) |
| { |
| inputTensorInfo.SetQuantizationScale(1.0f); |
| inputTensorInfo.SetQuantizationOffset(0); |
| } |
| |
| armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); |
| |
| std::vector<float> inputValues({ 1.0f, 2.0f, 3.0f, 4.0f, |
| 5.0f, 6.0f, 7.0f, 8.0f, |
| |
| 10.0f, 20.0f, 30.0f, 40.0f, |
| 50.0f, 60.0f, 70.0f, 80.0f, |
| |
| 100.0f, 200.0f, 300.0f, 400.0f, |
| 500.0f, 600.0f, 700.0f, 800.0f }); |
| std::vector<float> outputValues({ 666.0f, 888.0f, 1110.0f, 1332.0f }); |
| |
| return ReduceTestCommon<ArmnnType>(workloadFactory, |
| memoryManager, |
| tensorHandleFactory, |
| inputTensorInfo, |
| outputTensorInfo, |
| inputValues, |
| outputValues, |
| { 1, 2 }, |
| armnn::ReduceOperation::Sum); |
| } |
| |
| // Explicit template specializations |
| |
| template LayerTestResult<float, 4> |
| ReduceSumSimpleTest<armnn::DataType::Float32>( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory); |
| |
| template LayerTestResult<float, 4> |
| ReduceSumSingleAxisTest1<armnn::DataType::Float32>( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory); |
| |
| template LayerTestResult<float, 4> |
| ReduceSumSingleAxisTest2<armnn::DataType::Float32>( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory); |
| |
| template LayerTestResult<float, 4> |
| ReduceSumSingleAxisTest3<armnn::DataType::Float32>( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory); |
| |
| template LayerTestResult<float, 4> |
| ReduceSumMultipleAxisTest<armnn::DataType::Float32>( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory); |