diff options
Diffstat (limited to 'src/backends/backendsCommon')
-rw-r--r-- | src/backends/backendsCommon/WorkloadData.cpp | 32 | ||||
-rwxr-xr-x | src/backends/backendsCommon/test/LayerTests.cpp | 81 | ||||
-rw-r--r-- | src/backends/backendsCommon/test/LayerTests.hpp | 20 | ||||
-rw-r--r-- | src/backends/backendsCommon/test/SpaceToBatchNdTestImpl.hpp | 243 |
4 files changed, 363 insertions, 13 deletions
diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp index 62cbd05c13..7c02947b32 100644 --- a/src/backends/backendsCommon/WorkloadData.cpp +++ b/src/backends/backendsCommon/WorkloadData.cpp @@ -749,21 +749,14 @@ void SpaceToBatchNdQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) c ValidateTensorNumDimensions(workloadInfo.m_InputTensorInfos[0], "SpaceToBatchNdQueueDescriptor", 4, "input"); ValidateTensorNumDimensions(workloadInfo.m_OutputTensorInfos[0], "SpaceToBatchNdQueueDescriptor", 4, "output"); - if (workloadInfo.m_InputTensorInfos[0].GetNumElements() != workloadInfo.m_OutputTensorInfos[0].GetNumElements()) - { - throw InvalidArgumentException("SpaceToBatchNdQueueDescriptor: Input tensor has " + - to_string(workloadInfo.m_InputTensorInfos[0].GetNumElements()) + " but output tensor has " + - to_string(workloadInfo.m_OutputTensorInfos[0].GetNumElements()) + " elements."); - } - if (m_Parameters.m_BlockShape.size() != 2) { - throw InvalidArgumentException("Block Shape must contains 2 spatial dimensions"); + throw InvalidArgumentException("Block Shape must contain 2 spatial dimensions"); } if (m_Parameters.m_BlockShape.size() != m_Parameters.m_PadList.size()) { - throw InvalidArgumentException("Pad List must contains the same number of dimensions as Block Shape."); + throw InvalidArgumentException("Pad List must contain the same number of dimensions as Block Shape."); } const TensorShape inputShape = workloadInfo.m_InputTensorInfos[0].GetShape(); @@ -771,10 +764,23 @@ void SpaceToBatchNdQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) c std::pair<unsigned int, unsigned int> heightPad = m_Parameters.m_PadList[0]; std::pair<unsigned int, unsigned int> widthPad = m_Parameters.m_PadList[1]; - if ((inputShape[m_Parameters.m_DataLayout.GetHeightIndex()] + heightPad.first + heightPad.second) - % m_Parameters.m_BlockShape[0] != 0 || - (inputShape[m_Parameters.m_DataLayout.GetWidthIndex()] + widthPad.first + widthPad.second) - % m_Parameters.m_BlockShape[1] != 0) + unsigned int inputHeight = inputShape[m_Parameters.m_DataLayout.GetHeightIndex()] + + heightPad.first + heightPad.second; + + unsigned int inputWidth = inputShape[m_Parameters.m_DataLayout.GetWidthIndex()] + + widthPad.first + widthPad.second; + + unsigned int numInputElements = inputShape[0] * inputHeight * inputWidth + * inputShape[m_Parameters.m_DataLayout.GetChannelsIndex()]; + + if (workloadInfo.m_OutputTensorInfos[0].GetNumElements() != numInputElements) + { + throw InvalidArgumentException("SpaceToBatchNdQueueDescriptor: Input tensor has " + + to_string(numInputElements) + " after padding but output tensor has " + + to_string(workloadInfo.m_OutputTensorInfos[0].GetNumElements()) + " elements."); + } + + if (inputHeight % m_Parameters.m_BlockShape[0] != 0 || inputWidth % m_Parameters.m_BlockShape[1] != 0) { throw InvalidArgumentException( "Input shape after padding must be divisible by Block Shape in all spatial dimensions"); diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp index 6b5fa726b8..cdc989fe6d 100755 --- a/src/backends/backendsCommon/test/LayerTests.cpp +++ b/src/backends/backendsCommon/test/LayerTests.cpp @@ -26,6 +26,7 @@ #include "Pooling2dTestImpl.hpp" #include "ReshapeTestImpl.hpp" #include "FullyConnectedTestImpl.hpp" +#include "SpaceToBatchNdTestImpl.hpp" #include "SplitterTestImpl.hpp" #include "SoftmaxTestImpl.hpp" #include "NormTestImpl.hpp" @@ -6088,3 +6089,83 @@ LayerTestResult<float, 4> AdditionAfterMaxPoolTest(armnn::IWorkloadFactory& work return addRet; } + +LayerTestResult<float, 4> SpaceToBatchNdSimpleFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdSimpleTest<float>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiChannelsTest<float>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdMultiBlockFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiBlockTest<float>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdPaddingFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdPaddingTest<float>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdSimpleTest<uint8_t>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiChannelsTest<uint8_t>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiBlockTest<uint8_t>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdPaddingTest<uint8_t>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdSimpleNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdSimpleNHWCTest<float>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiChannelsNHWCTest<float>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdMultiBlockNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiBlockNHWCTest<float>(workloadFactory); +} + +LayerTestResult<float, 4> SpaceToBatchNdPaddingNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdPaddingNHWCTest<float>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdSimpleNHWCTest<uint8_t>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiChannelsNHWCTest<uint8_t>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdMultiBlockNHWCTest<uint8_t>(workloadFactory); +} + +LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory) +{ + return SpaceToBatchNdPaddingNHWCTest<uint8_t>(workloadFactory); +} diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp index 57383d3276..66032c8f2a 100644 --- a/src/backends/backendsCommon/test/LayerTests.hpp +++ b/src/backends/backendsCommon/test/LayerTests.hpp @@ -414,3 +414,23 @@ LayerTestResult<float, 3> MeanVtsFloat2Test(armnn::IWorkloadFactory& workloadFac LayerTestResult<float, 3> MeanVtsFloat3Test(armnn::IWorkloadFactory& workloadFactory); LayerTestResult<float, 4> AdditionAfterMaxPoolTest(armnn::IWorkloadFactory& workloadFactory); + +LayerTestResult<float, 4> SpaceToBatchNdSimpleFloat32Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsFloat32Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<float, 4> SpaceToBatchNdMultiBlockFloat32Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<float, 4> SpaceToBatchNdPaddingFloat32Test(armnn::IWorkloadFactory& workloadFactory); + +LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleUint8Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsUint8Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockUint8Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingUint8Test(armnn::IWorkloadFactory& workloadFactory); + +LayerTestResult<float, 4> SpaceToBatchNdSimpleNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<float, 4> SpaceToBatchNdMultiBlockNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<float, 4> SpaceToBatchNdPaddingNHWCFloat32Test(armnn::IWorkloadFactory& workloadFactory); + +LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory); +LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingNHWCUint8Test(armnn::IWorkloadFactory& workloadFactory); 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 <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); +} |