| // |
| // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include <ResolveType.hpp> |
| |
| #include <armnn/backends/IBackendInternal.hpp> |
| #include <armnn/backends/WorkloadFactory.hpp> |
| |
| #include <DataTypeUtils.hpp> |
| #include <armnnTestUtils/LayerTestResult.hpp> |
| #include <armnnTestUtils/TensorCopyUtils.hpp> |
| #include <armnnTestUtils/TensorHelpers.hpp> |
| #include <armnnTestUtils/WorkloadTestUtils.hpp> |
| |
| namespace |
| { |
| |
| template<armnn::DataType ArmnnType, |
| std::size_t InputDim, |
| std::size_t OutputDim, |
| typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, OutputDim> BatchToSpaceNdHelper( |
| armnn::IWorkloadFactory &workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory, |
| const armnn::DataLayout& dataLayout, |
| const unsigned int *inputShape, |
| const std::vector<float> &inputData, |
| const std::vector<unsigned int> &blockShape, |
| const std::vector<std::pair<unsigned int, unsigned int>> &crops, |
| const unsigned int *outputShape, |
| const std::vector<float> &outputData, |
| float scale = 1.0f, |
| int32_t offset = 0) |
| { |
| IgnoreUnused(memoryManager); |
| |
| armnn::TensorInfo inputTensorInfo(InputDim, inputShape, ArmnnType); |
| armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, ArmnnType); |
| |
| inputTensorInfo.SetQuantizationScale(scale); |
| inputTensorInfo.SetQuantizationOffset(offset); |
| |
| outputTensorInfo.SetQuantizationScale(scale); |
| outputTensorInfo.SetQuantizationOffset(offset); |
| |
| std::vector<T> input = ConvertToDataType<ArmnnType>(inputData, inputTensorInfo); |
| |
| std::vector<T> actualOutput(outputTensorInfo.GetNumElements()); |
| std::vector<T> expectedOutput = ConvertToDataType<ArmnnType>(outputData, outputTensorInfo); |
| |
| std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); |
| std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); |
| |
| armnn::BatchToSpaceNdQueueDescriptor data; |
| data.m_Parameters.m_DataLayout = dataLayout; |
| data.m_Parameters.m_BlockShape = blockShape; |
| data.m_Parameters.m_Crops = crops; |
| armnn::WorkloadInfo info; |
| AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); |
| AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); |
| |
| std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateWorkload(armnn::LayerType::BatchToSpaceNd, |
| data, info); |
| |
| inputHandle->Allocate(); |
| outputHandle->Allocate(); |
| |
| CopyDataToITensorHandle(inputHandle.get(), input.data()); |
| |
| workload->PostAllocationConfigure(); |
| workload->Execute(); |
| |
| CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); |
| |
| return LayerTestResult<T, OutputDim>(actualOutput, |
| expectedOutput, |
| outputHandle->GetShape(), |
| outputTensorInfo.GetShape()); |
| } |
| |
| } // anonymous namespace |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest1( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 2, 2, 1}; |
| const unsigned int outputShape[] = {1, 4, 4, 1}; |
| |
| std::vector<float> input({ |
| // Batch 0, Height 0, Width (2) x Channel (1) |
| 1.0f, 3.0f, |
| // Batch 0, Height 1, Width (2) x Channel (1) |
| 9.0f, 11.0f, |
| |
| |
| // Batch 1, Height 0, Width (2) x Channel (1) |
| 2.0f, 4.0f, |
| // Batch 1, Height 1, Width (2) x Channel (1) |
| 10.0f, 12.0f, |
| |
| |
| // Batch 2, Height 0, Width (2) x Channel (1) |
| 5.0f, 7.0f, |
| // Batch 2, Height 1, Width (2) x Channel (1) |
| 13.0f, 15.0f, |
| |
| // Batch 3, Height 0, Width (2) x Channel (3) |
| 6.0f, 8.0f, |
| // Batch 3, Height 1, Width (2) x Channel (1) |
| 14.0f, 16.0f |
| }); |
| |
| std::vector<float> expectedOutput({ |
| 1.0f, 2.0f, 3.0f, 4.0f, |
| 5.0f, 6.0f, 7.0f, 8.0f, |
| 9.0f, 10.0f, 11.0f, 12.0f, |
| 13.0f, 14.0f, 15.0f, 16.0f |
| }); |
| |
| std::vector<unsigned int> blockShape {2, 2}; |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest2( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 1, 1, 1}; |
| const unsigned int outputShape[] = {1, 2, 2, 1}; |
| |
| std::vector<float> input({ |
| // Batch 0, Height 0, Width (2) x Channel (1) |
| 1.0f, 2.0f, 3.0f, 4.0f |
| }); |
| |
| std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest3( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 1, 1, 3}; |
| const unsigned int outputShape[] = {1, 2, 2, 3}; |
| |
| std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f}); |
| |
| std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest4( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {8, 1, 3, 1}; |
| const unsigned int outputShape[] = {2, 2, 4, 1}; |
| |
| std::vector<float> input({ |
| 0.0f, 1.0f, 3.0f, |
| 0.0f, 9.0f, 11.0f, |
| 0.0f, 2.0f, 4.0f, |
| 0.0f, 10.0f, 12.0f, |
| 0.0f, 5.0f, 7.0f, |
| 0.0f, 13.0f, 15.0f, |
| 0.0f, 6.0f, 8.0f, |
| 0.0f, 14.0f, 16.0f |
| }); |
| |
| std::vector<float> expectedOutput({ |
| 1.0f, 2.0f, 3.0f, 4.0f, |
| 5.0f, 6.0f, 7.0f, 8.0f, |
| 9.0f, 10.0f, 11.0f, 12.0f, |
| 13.0f, 14.0f, 15.0f, 16.0f |
| }); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest5( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 2, 2, 1}; |
| const unsigned int outputShape[] = {1, 4, 4, 1}; |
| |
| std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}); |
| std::vector<float> expectedOutput({1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, |
| input, blockShape, crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest6( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 1, 1, 1}; |
| const unsigned int outputShape[] = {1, 2, 2, 1}; |
| |
| std::vector<float> input({ |
| // Batch 0, Height 0, Width (2) x Channel (1) |
| 1, 2, 3, 4 |
| }); |
| |
| std::vector<float> expectedOutput({1, 2, 3, 4}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNhwcTest7( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 1, 1, 3}; |
| const unsigned int outputShape[] = {1, 2, 2, 3}; |
| |
| std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}); |
| |
| std::vector<float> expectedOutput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NHWC, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest1( |
| armnn::IWorkloadFactory &workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 3, 1, 1}; |
| const unsigned int outputShape[] = {1, 3, 2, 2}; |
| |
| std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f}); |
| |
| std::vector<float> expectedOutput({ |
| // Batch 0, Channel 0, Height (2) x Width (2) |
| 1.0f, 4.0f, |
| 7.0f, 10.0f, |
| |
| // Batch 0, Channel 1, Height (2) x Width (2) |
| 2.0f, 5.0f, |
| 8.0f, 11.0f, |
| |
| // Batch 0, Channel 2, Height (2) x Width (2) |
| 3.0f, 6.0f, |
| 9.0f, 12.0f, |
| }); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest2( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 1, 1, 1}; |
| const unsigned int outputShape[] = {1, 1, 2, 2}; |
| |
| std::vector<float> input({ |
| // Batch 0, Height 0, Width (2) x Channel (1) |
| 1.0f, 2.0f, 3.0f, 4.0f |
| }); |
| |
| std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest3( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 3, 1, 1}; |
| const unsigned int outputShape[] = {1, 3, 2, 2}; |
| |
| std::vector<float> input({1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f}); |
| |
| std::vector<float> expectedOutput({ |
| // Batch 0, Channel 0, Height (2) x Width (2) |
| 1.0f, 7.0f, |
| 2.0f, 8.0f, |
| |
| // Batch 0, Channel 1, Height (2) x Width (2) |
| 3.0f, 9.0f, |
| 4.0f, 10.0f, |
| |
| // Batch 0, Channel 2, Height (2) x Width (2) |
| 5.0f, 11.0f, |
| 6.0f, 12.0f, |
| }); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest4( |
| armnn::IWorkloadFactory &workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 3, 1, 1}; |
| const unsigned int outputShape[] = {1, 3, 2, 2}; |
| |
| std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}); |
| |
| std::vector<float> expectedOutput({ |
| // Batch 0, Channel 0, Height (2) x Width (2) |
| 1, 4, |
| 7, 10, |
| |
| // Batch 0, Channel 1, Height (2) x Width (2) |
| 2, 5, |
| 8, 11, |
| |
| // Batch 0, Channel 2, Height (2) x Width (2) |
| 3, 6, |
| 9, 12, |
| }); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest5( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 1, 1, 1}; |
| const unsigned int outputShape[] = {1, 1, 2, 2}; |
| |
| std::vector<float> input({ |
| // Batch 0, Height 0, Width (2) x Channel (1) |
| 1, 2, 3, 4 |
| }); |
| |
| std::vector<float> expectedOutput({1, 2, 3, 4}); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest6( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {4, 3, 1, 1}; |
| const unsigned int outputShape[] = {1, 3, 2, 2}; |
| |
| std::vector<float> input({1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12}); |
| |
| std::vector<float> expectedOutput({ |
| // Batch 0, Channel 0, Height (2) x Width (2) |
| 1, 7, |
| 2, 8, |
| |
| // Batch 0, Channel 1, Height (2) x Width (2) |
| 3, 9, |
| 4, 10, |
| |
| // Batch 0, Channel 2, Height (2) x Width (2) |
| 5, 11, |
| 6, 12, |
| }); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |
| |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| LayerTestResult<T, 4> BatchToSpaceNdNchwTest7( |
| armnn::IWorkloadFactory& workloadFactory, |
| const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, |
| const armnn::ITensorHandleFactory& tensorHandleFactory) |
| { |
| const unsigned int inputShape[] = {8, 1, 1, 3}; |
| const unsigned int outputShape[] = {2, 1, 2, 4}; |
| |
| std::vector<float> input({ |
| 0, 1, 3, 0, 9, 11, |
| 0, 2, 4, 0, 10, 12, |
| 0, 5, 7, 0, 13, 15, |
| 0, 6, 8, 0, 14, 16 |
| }); |
| |
| std::vector<float> expectedOutput({ |
| 1, 2, 3, 4, |
| 5, 6, 7, 8, |
| 9, 10, 11, 12, |
| 13, 14, 15, 16 |
| }); |
| |
| std::vector<unsigned int> blockShape({2, 2}); |
| std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}}; |
| |
| return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, tensorHandleFactory, |
| armnn::DataLayout::NCHW, inputShape, input, blockShape, |
| crops, outputShape, expectedOutput); |
| } |