From 3ea76d5f0d99794cf5f0b60ef3738d0905f10b2a Mon Sep 17 00:00:00 2001 From: Nattapat Chaimanowong Date: Fri, 9 Nov 2018 14:10:38 +0000 Subject: IVGCVSW-2095 Add reference implementation and unit tests for SpaceToBatchNd Change-Id: I27ffebdece6e68460931a44c15b9b029f9fce638 --- .../backendsCommon/test/SpaceToBatchNdTestImpl.hpp | 243 +++++++++++++++++++++ 1 file changed, 243 insertions(+) create mode 100644 src/backends/backendsCommon/test/SpaceToBatchNdTestImpl.hpp (limited to 'src/backends/backendsCommon/test/SpaceToBatchNdTestImpl.hpp') diff --git a/src/backends/backendsCommon/test/SpaceToBatchNdTestImpl.hpp b/src/backends/backendsCommon/test/SpaceToBatchNdTestImpl.hpp new file mode 100644 index 0000000000..5dd21bf3c6 --- /dev/null +++ b/src/backends/backendsCommon/test/SpaceToBatchNdTestImpl.hpp @@ -0,0 +1,243 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// +#pragma once + +#include +#include +#include + +#include +#include + +#include + +template +LayerTestResult SpaceToBatchNdTestImpl( + const armnn::IWorkloadFactory& workloadFactory, + armnn::TensorInfo& inputTensorInfo, + armnn::TensorInfo& outputTensorInfo, + std::vector& inputData, + std::vector& 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 inputTmp(inputData.size()); + armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), inputTmp.data()); + inputData = inputTmp; + + std::vector outputTmp(outputExpectedData.size()); + armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputExpectedData.data(), outputTmp.data()); + outputExpectedData = outputTmp; + } + + if(armnn::IsQuantizedType()) + { + inputTensorInfo.SetQuantizationScale(qScale); + inputTensorInfo.SetQuantizationOffset(qOffset); + outputTensorInfo.SetQuantizationScale(qScale); + outputTensorInfo.SetQuantizationOffset(qOffset); + } + + boost::multi_array input = MakeTensor(inputTensorInfo, QuantizedVector(qScale, qOffset, inputData)); + + LayerTestResult ret(outputTensorInfo); + ret.outputExpected = MakeTensor(outputTensorInfo, QuantizedVector(qScale, qOffset, outputExpectedData)); + + std::unique_ptr inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::WorkloadInfo info; + AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr 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 +LayerTestResult 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()); + outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType()); + + std::vector input = std::vector( + { + 1.0f, 2.0f, 3.0f, 4.0f + }); + + std::vector outputExpected = std::vector( + { + 1.0f, 2.0f, 3.0f, 4.0f + }); + + return SpaceToBatchNdTestImpl(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); +} + +template +LayerTestResult 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()); + outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType()); + + std::vector input = std::vector( + { + 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 outputExpected = std::vector( + { + 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(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); +} + +template +LayerTestResult 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()); + outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType()); + + std::vector input = std::vector( + { + 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 outputExpected = std::vector( + { + 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(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); +} + +template +LayerTestResult 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()); + outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::GetDataType()); + + std::vector input = std::vector( + { + 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 outputExpected = std::vector( + { + 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(workloadFactory, inputTensorInfo, outputTensorInfo, input, outputExpected, desc); +} + +template +LayerTestResult SpaceToBatchNdSimpleNHWCTest(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdSimpleTest(workloadFactory, armnn::DataLayout::NHWC); +} + +template +LayerTestResult SpaceToBatchNdMultiChannelsNHWCTest(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiChannelsTest(workloadFactory, armnn::DataLayout::NHWC); +} + +template +LayerTestResult SpaceToBatchNdMultiBlockNHWCTest(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiBlockTest(workloadFactory, armnn::DataLayout::NHWC); +} + +template +LayerTestResult SpaceToBatchNdPaddingNHWCTest(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdPaddingTest(workloadFactory, armnn::DataLayout::NHWC); +} -- cgit v1.2.1