| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #pragma once |
| |
| #include <armnn/ArmNN.hpp> |
| #include <armnn/Tensor.hpp> |
| #include <armnn/TypesUtils.hpp> |
| |
| #include <backendsCommon/CpuTensorHandle.hpp> |
| #include <backendsCommon/WorkloadFactory.hpp> |
| |
| #include <test/TensorHelpers.hpp> |
| |
| template<typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdTestImpl( |
| const armnn::IWorkloadFactory& workloadFactory, |
| armnn::TensorInfo& inputTensorInfo, |
| armnn::TensorInfo& outputTensorInfo, |
| std::vector<float>& inputData, |
| std::vector<float>& outputExpectedData, |
| armnn::SpaceToBatchNdQueueDescriptor descriptor, |
| const float qScale = 1.0f, |
| const int32_t qOffset = 0) |
| { |
| const armnn::PermutationVector NCHWToNHWC = {0, 3, 1, 2}; |
| if (descriptor.m_Parameters.m_DataLayout == armnn::DataLayout::NHWC) |
| { |
| inputTensorInfo = armnnUtils::Permuted(inputTensorInfo, NCHWToNHWC); |
| outputTensorInfo = armnnUtils::Permuted(outputTensorInfo, NCHWToNHWC); |
| |
| std::vector<float> inputTmp(inputData.size()); |
| armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), inputTmp.data()); |
| inputData = inputTmp; |
| |
| std::vector<float> outputTmp(outputExpectedData.size()); |
| armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputExpectedData.data(), outputTmp.data()); |
| outputExpectedData = outputTmp; |
| } |
| |
| if(armnn::IsQuantizedType<T>()) |
| { |
| inputTensorInfo.SetQuantizationScale(qScale); |
| inputTensorInfo.SetQuantizationOffset(qOffset); |
| outputTensorInfo.SetQuantizationScale(qScale); |
| outputTensorInfo.SetQuantizationOffset(qOffset); |
| } |
| |
| boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData)); |
| |
| LayerTestResult<T, 4> ret(outputTensorInfo); |
| ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData)); |
| |
| std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); |
| std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); |
| |
| armnn::WorkloadInfo info; |
| AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); |
| AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); |
| |
| std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSpaceToBatchNd(descriptor, info); |
| |
| inputHandle->Allocate(); |
| outputHandle->Allocate(); |
| |
| CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]); |
| |
| workload->Execute(); |
| |
| CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); |
| |
| return ret; |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdSimpleTest(armnn::IWorkloadFactory& workloadFactory, |
| armnn::DataLayout dataLayout = armnn::DataLayout::NCHW) |
| { |
| armnn::TensorInfo inputTensorInfo; |
| armnn::TensorInfo outputTensorInfo; |
| |
| unsigned int inputShape[] = {1, 1, 2, 2}; |
| unsigned int outputShape[] = {4, 1, 1, 1}; |
| |
| armnn::SpaceToBatchNdQueueDescriptor desc; |
| desc.m_Parameters.m_DataLayout = dataLayout; |
| desc.m_Parameters.m_BlockShape = {2, 2}; |
| desc.m_Parameters.m_PadList = {{0, 0}, {0, 0}}; |
| |
| inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>()); |
| outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>()); |
| |
| std::vector<float> input = std::vector<float>( |
| { |
| 1.0f, 2.0f, 3.0f, 4.0f |
| }); |
| |
| std::vector<float> outputExpected = std::vector<float>( |
| { |
| 1.0f, 2.0f, 3.0f, 4.0f |
| }); |
| |
| return SpaceToBatchNdTestImpl<T>(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdMultiChannelsTest(armnn::IWorkloadFactory& workloadFactory, |
| armnn::DataLayout dataLayout = armnn::DataLayout::NCHW) |
| { |
| armnn::TensorInfo inputTensorInfo; |
| armnn::TensorInfo outputTensorInfo; |
| |
| unsigned int inputShape[] = {1, 3, 2, 2}; |
| unsigned int outputShape[] = {4, 3, 1, 1}; |
| |
| armnn::SpaceToBatchNdQueueDescriptor desc; |
| desc.m_Parameters.m_DataLayout = dataLayout; |
| desc.m_Parameters.m_BlockShape = {2, 2}; |
| desc.m_Parameters.m_PadList = {{0, 0}, {0, 0}}; |
| |
| inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>()); |
| outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>()); |
| |
| std::vector<float> input = std::vector<float>( |
| { |
| 1.0f, 4.0f, 7.0f, 10.0f, |
| 2.0f, 5.0, 8.0, 11.0f, |
| 3.0f, 6.0f, 9.0f, 12.0f |
| }); |
| |
| std::vector<float> outputExpected = std::vector<float>( |
| { |
| 1.0f, 2.0f, 3.0f, |
| 4.0f, 5.0f, 6.0f, |
| 7.0f, 8.0f, 9.0f, |
| 10.0f, 11.0f, 12.0f |
| }); |
| |
| return SpaceToBatchNdTestImpl<T>(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdMultiBlockTest(armnn::IWorkloadFactory& workloadFactory, |
| armnn::DataLayout dataLayout = armnn::DataLayout::NCHW) |
| { |
| armnn::TensorInfo inputTensorInfo; |
| armnn::TensorInfo outputTensorInfo; |
| |
| unsigned int inputShape[] = {1, 1, 4, 4}; |
| unsigned int outputShape[] = {4, 1, 2, 2}; |
| |
| armnn::SpaceToBatchNdQueueDescriptor desc; |
| desc.m_Parameters.m_DataLayout = dataLayout; |
| desc.m_Parameters.m_BlockShape = {2, 2}; |
| desc.m_Parameters.m_PadList = {{0, 0}, {0, 0}}; |
| |
| inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>()); |
| outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>()); |
| |
| std::vector<float> input = std::vector<float>( |
| { |
| 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<float> outputExpected = std::vector<float>( |
| { |
| 1.0f, 3.0f, 9.0f, 11.0f, |
| 2.0f, 4.0f, 10.0f, 12.0f, |
| 5.0f, 7.0f, 13.0f, 15.0f, |
| 6.0f, 8.0f, 14.0f, 16.0f |
| }); |
| |
| return SpaceToBatchNdTestImpl<T>(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdPaddingTest(armnn::IWorkloadFactory& workloadFactory, |
| armnn::DataLayout dataLayout = armnn::DataLayout::NCHW) |
| { |
| armnn::TensorInfo inputTensorInfo; |
| armnn::TensorInfo outputTensorInfo; |
| |
| unsigned int inputShape[] = {2, 1, 2, 4}; |
| unsigned int outputShape[] = {8, 1, 1, 3}; |
| |
| armnn::SpaceToBatchNdQueueDescriptor desc; |
| desc.m_Parameters.m_DataLayout = dataLayout; |
| desc.m_Parameters.m_BlockShape = {2, 2}; |
| desc.m_Parameters.m_PadList = {{0, 0}, {2, 0}}; |
| |
| inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::GetDataType<T>()); |
| outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType<T>()); |
| |
| std::vector<float> input = std::vector<float>( |
| { |
| 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<float> outputExpected = std::vector<float>( |
| { |
| 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 |
| }); |
| |
| return SpaceToBatchNdTestImpl<T>(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdSimpleNHWCTest(armnn::IWorkloadFactory& workloadFactory) |
| { |
| return SpaceToBatchNdSimpleTest<T>(workloadFactory, armnn::DataLayout::NHWC); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdMultiChannelsNHWCTest(armnn::IWorkloadFactory& workloadFactory) |
| { |
| return SpaceToBatchNdMultiChannelsTest<T>(workloadFactory, armnn::DataLayout::NHWC); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdMultiBlockNHWCTest(armnn::IWorkloadFactory& workloadFactory) |
| { |
| return SpaceToBatchNdMultiBlockTest<T>(workloadFactory, armnn::DataLayout::NHWC); |
| } |
| |
| template <typename T> |
| LayerTestResult<T, 4> SpaceToBatchNdPaddingNHWCTest(armnn::IWorkloadFactory& workloadFactory) |
| { |
| return SpaceToBatchNdPaddingTest<T>(workloadFactory, armnn::DataLayout::NHWC); |
| } |