From 8800c00770ed14eb48045cfcf033d6b67595a126 Mon Sep 17 00:00:00 2001 From: Matthew Bentham Date: Mon, 19 Nov 2018 13:19:28 +0000 Subject: IVGCVSW-2169 Remove DataLayoutIndexed from public API Change-Id: If8d8087d9d365e467d3ca9bf9c40d7219cb75cfd --- .../backendsCommon/test/Conv2dTestImpl.hpp | 41 ++++++----- src/backends/backendsCommon/test/LayerTests.cpp | 86 +++++++++++----------- src/backends/backendsCommon/test/LayerTests.hpp | 54 +++++++------- .../backendsCommon/test/Pooling2dTestImpl.hpp | 21 +++--- 4 files changed, 102 insertions(+), 100 deletions(-) (limited to 'src/backends/backendsCommon/test') diff --git a/src/backends/backendsCommon/test/Conv2dTestImpl.hpp b/src/backends/backendsCommon/test/Conv2dTestImpl.hpp index d99b7f7fa3..6685a8edd2 100755 --- a/src/backends/backendsCommon/test/Conv2dTestImpl.hpp +++ b/src/backends/backendsCommon/test/Conv2dTestImpl.hpp @@ -14,6 +14,7 @@ #include #include "QuantizeHelper.hpp" +#include #include #include #include @@ -75,7 +76,7 @@ LayerTestResult SimpleConvolution2dTestImpl( const boost::multi_array& originalOutputExpected, float qScale, int32_t qOffset, - const armnn::DataLayoutIndexed& layout = armnn::DataLayout::NCHW, + const armnn::DataLayout layout = armnn::DataLayout::NCHW, uint32_t padLeft = 0, uint32_t padTop = 0, uint32_t padRight = 0, @@ -137,7 +138,7 @@ LayerTestResult SimpleConvolution2dTestImpl( // at this point if we require it permute the input data const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -166,7 +167,7 @@ LayerTestResult SimpleConvolution2dTestImpl( outputData.insert(outputData.end(), outputImage.begin(), outputImage.end()); // at this point if we require it permute the expected output - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(outputData.size()); armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data()); @@ -187,7 +188,7 @@ LayerTestResult SimpleConvolution2dTestImpl( armnn::ScopedCpuTensorHandle biasTensor(biasDesc); // Permute the kernel if necessary boost::multi_array kernel = boost::multi_array(originalKernel); - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernel.data(), kernel.data()); } @@ -210,7 +211,7 @@ LayerTestResult SimpleConvolution2dTestImpl( data.m_Parameters.m_PadTop = padTop; data.m_Parameters.m_PadBottom = padBottom; data.m_Parameters.m_BiasEnabled = biasEnabled; - data.m_Parameters.m_DataLayout = layout.GetDataLayout(); + data.m_Parameters.m_DataLayout = layout; std::unique_ptr workload = workloadFactory.CreateConvolution2d(data, info); inputHandle->Allocate(); @@ -327,7 +328,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTestImpl( const boost::multi_array& outputExpected, float qScale, int32_t qOffset, - const armnn::DataLayoutIndexed& layout, + const armnn::DataLayout layout, uint32_t padLeft = 0, uint32_t padTop = 0, uint32_t padRight = 0, @@ -377,7 +378,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTestImpl( // At this point if we require it permute the input data const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -401,7 +402,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTestImpl( LayerTestResult ret(outputTensorInfo); // At this point if we require it permute the expected output - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(outputData.size()); armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data()); @@ -417,7 +418,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTestImpl( // Permute the kernel if necessary boost::multi_array kernel = boost::multi_array(originalKernel); - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernel.data(), kernel.data()); } @@ -440,7 +441,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTestImpl( data.m_Parameters.m_PadTop = padTop; data.m_Parameters.m_PadBottom = padBottom; data.m_Parameters.m_BiasEnabled = biasEnabled; - data.m_Parameters.m_DataLayout = layout.GetDataLayout(); + data.m_Parameters.m_DataLayout = layout; armnn::WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); @@ -466,7 +467,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1TestImpl( float qScale, int32_t qOffset, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { unsigned int inputHeight = 3; unsigned int inputWidth = 3; @@ -511,7 +512,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1TestImpl( })); // at this point if we require it permute the input data const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -533,7 +534,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1TestImpl( 0.f, 0.f, 0.f, -1.f, 0.f, -1.f, })); - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(kernelData.size()); armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, kernelData.data(), tmp.data()); @@ -557,7 +558,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1TestImpl( } LayerTestResult ret(outputTensorInfo); - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(outputImage.size()); armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputImage.data(), tmp.data()); @@ -589,7 +590,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1TestImpl( data.m_Parameters.m_PadTop = 0; data.m_Parameters.m_PadBottom = 0; data.m_Parameters.m_BiasEnabled = biasEnabled; - data.m_Parameters.m_DataLayout = layout.GetDataLayout(); + data.m_Parameters.m_DataLayout = layout; std::unique_ptr workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); inputHandle->Allocate(); @@ -611,7 +612,7 @@ LayerTestResult DepthwiseConvolution2dTestImpl( float qScale, int32_t qOffset, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { unsigned int depthMultiplier = 2; @@ -672,7 +673,7 @@ LayerTestResult DepthwiseConvolution2dTestImpl( std::vector inputData = originalInputData; // at this point if we require it permute the input data const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, originalInputData.data(), inputData.data()); } @@ -709,7 +710,7 @@ LayerTestResult DepthwiseConvolution2dTestImpl( 0, 0, 0 })); std::vector kernelData = originalKernelData; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernelData.data(), kernelData.data()); } @@ -762,7 +763,7 @@ LayerTestResult DepthwiseConvolution2dTestImpl( LayerTestResult ret(outputTensorInfo); std::vector outputImage = originalOutputImage; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, originalOutputImage.data(), outputImage.data()); } @@ -792,7 +793,7 @@ LayerTestResult DepthwiseConvolution2dTestImpl( data.m_Parameters.m_PadTop = 1; data.m_Parameters.m_PadBottom = 1; data.m_Parameters.m_BiasEnabled = biasEnabled; - data.m_Parameters.m_DataLayout = layout.GetDataLayout(); + data.m_Parameters.m_DataLayout = layout; std::unique_ptr workload = workloadFactory.CreateDepthwiseConvolution2d(data, info); inputHandle->Allocate(); diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp index caa4f4065d..ecd09ca024 100755 --- a/src/backends/backendsCommon/test/LayerTests.cpp +++ b/src/backends/backendsCommon/test/LayerTests.cpp @@ -109,7 +109,7 @@ LayerTestResult SimpleConvolution2d3x5TestCommon( float qScale, int32_t qOffset, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Use common single-batch 3-channel 16x8 image. armnn::TensorInfo inputDesc({1, 3, 8, 16}, armnn::GetDataType()); @@ -192,7 +192,7 @@ LayerTestResult SimpleConvolution2d3x3TestCommon( float qScale, int32_t qOffset, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Use a 3x3 kernel, which exercises ArmCompute's direct convolution path. @@ -315,7 +315,7 @@ LayerTestResult SimpleConvolution2d3x5Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return SimpleConvolution2d3x5TestCommon(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout); } @@ -324,7 +324,7 @@ LayerTestResult SimpleConvolution2d3x5Uint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return SimpleConvolution2d3x5TestCommon(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); } @@ -333,7 +333,7 @@ LayerTestResult SimpleConvolution2d3x3Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return SimpleConvolution2d3x3TestCommon(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout); } @@ -355,7 +355,7 @@ LayerTestResult SimpleConvolution2d3x3Uint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return SimpleConvolution2d3x3TestCommon(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); } @@ -364,7 +364,7 @@ template LayerTestResult Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout, + const armnn::DataLayout layout, float qScale, int32_t qOffset) { @@ -426,7 +426,7 @@ template LayerTestResult SimpleConvolution2dAsymmetricPaddingTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout, + const armnn::DataLayout layout, float qScale, int32_t qOffset) { @@ -485,7 +485,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTestCommon( float qScale, int32_t qOffset, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Use a single-batch 2-channel 5x5 image as input. armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5 }, armnn::GetDataType()); @@ -673,7 +673,7 @@ LayerTestResult Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon( workloadFactory, memoryManager, layout, 0.0f, 0); @@ -682,7 +682,7 @@ Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( LayerTestResult Convolution2dAsymmetricPaddingTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return SimpleConvolution2dAsymmetricPaddingTestCommon( workloadFactory, memoryManager, layout, 0.0f, 0); @@ -692,7 +692,7 @@ LayerTestResult DepthwiseConvolution2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return DepthwiseConvolution2dTestImpl( workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); @@ -710,7 +710,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return DepthwiseConvolution2dDepthMul1TestImpl( workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); @@ -720,7 +720,7 @@ LayerTestResult DepthwiseConvolution2dAsymmetricTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return DepthwiseConvolution2dAsymmetricTestCommon( workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout); @@ -730,7 +730,7 @@ LayerTestResult DepthwiseConvolution2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return DepthwiseConvolution2dTestImpl( workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); @@ -740,7 +740,7 @@ LayerTestResult DepthwiseConvolution2dDepthMul1Uint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return DepthwiseConvolution2dDepthMul1TestImpl( workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout); @@ -775,7 +775,7 @@ LayerTestResult CompareDepthwiseConvolution2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, armnn::IWorkloadFactory& refWorkloadFactory, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { return CompareDepthwiseConvolution2dTestImpl(workloadFactory, memoryManager, refWorkloadFactory, layout); } @@ -784,13 +784,13 @@ template LayerTestResult CompareDepthwiseConvolution2dTest( armnn::IWorkloadFactory&, const armnn::IBackendInternal::IMemoryManagerSharedPtr&, armnn::IWorkloadFactory&, - const armnn::DataLayoutIndexed&); + const armnn::DataLayout); template LayerTestResult CompareDepthwiseConvolution2dTest( armnn::IWorkloadFactory&, const armnn::IBackendInternal::IMemoryManagerSharedPtr&, armnn::IWorkloadFactory&, - const armnn::DataLayoutIndexed&); + const armnn::DataLayout); LayerTestResult SimpleNormalizationAcrossTest( armnn::IWorkloadFactory& workloadFactory, @@ -3857,7 +3857,7 @@ LayerTestResult Concatenation4dDiffShapeDim3Test( LayerTestResult ResizeBilinearNopTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { const armnn::TensorInfo inputTensorInfo = GetTensorInfo(1, 2, 4, 4, dataLayout); const armnn::TensorInfo outputTensorInfo = GetTensorInfo(1, 2, 4, 4, dataLayout); @@ -3875,7 +3875,7 @@ LayerTestResult ResizeBilinearNopTest( }); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -3911,7 +3911,7 @@ LayerTestResult ResizeBilinearNopTest( LayerTestResult SimpleResizeBilinearTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { const armnn::TensorInfo inputTensorInfo = GetTensorInfo(1, 2, 2, 2, dataLayout); const armnn::TensorInfo outputTensorInfo = GetTensorInfo(1, 2, 1, 1, dataLayout); @@ -3937,7 +3937,7 @@ LayerTestResult SimpleResizeBilinearTest( }); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -3977,7 +3977,7 @@ LayerTestResult SimpleResizeBilinearTest( LayerTestResult ResizeBilinearSqMinTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { const armnn::TensorInfo inputTensorInfo = GetTensorInfo(1, 2, 4, 4, dataLayout); const armnn::TensorInfo outputTensorInfo = GetTensorInfo(1, 2, 2, 2, dataLayout); @@ -4003,7 +4003,7 @@ LayerTestResult ResizeBilinearSqMinTest( }); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -4043,7 +4043,7 @@ LayerTestResult ResizeBilinearSqMinTest( LayerTestResult ResizeBilinearMinTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { const armnn::TensorInfo inputTensorInfo = GetTensorInfo(1, 2, 3, 5, dataLayout); const armnn::TensorInfo outputTensorInfo = GetTensorInfo(1, 2, 2, 3, dataLayout); @@ -4067,7 +4067,7 @@ LayerTestResult ResizeBilinearMinTest( }); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -4107,7 +4107,7 @@ LayerTestResult ResizeBilinearMinTest( LayerTestResult ResizeBilinearMagTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { const armnn::TensorInfo inputTensorInfo = GetTensorInfo(1, 2, 3, 2, dataLayout); const armnn::TensorInfo outputTensorInfo = GetTensorInfo(1, 2, 3, 5, dataLayout); @@ -4133,7 +4133,7 @@ LayerTestResult ResizeBilinearMagTest( }); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -4235,7 +4235,7 @@ LayerTestResult L2NormalizationTestImpl( const armnn::TensorShape& inputOutputTensorShape, const std::vector& inputValues, const std::vector& expectedOutputValues, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32); const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32); @@ -4243,7 +4243,7 @@ LayerTestResult L2NormalizationTestImpl( // at this point if we require it permute the input data const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; std::vector inputData = inputValues; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -4254,7 +4254,7 @@ LayerTestResult L2NormalizationTestImpl( LayerTestResult result(outputTensorInfo); std::vector expectedOutputData = expectedOutputValues; - if (layout.GetDataLayout() == armnn::DataLayout::NHWC) + if (layout == armnn::DataLayout::NHWC) { std::vector tmp(expectedOutputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, expectedOutputData.data(), tmp.data()); @@ -4266,7 +4266,7 @@ LayerTestResult L2NormalizationTestImpl( std::unique_ptr outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); armnn::L2NormalizationQueueDescriptor descriptor; - descriptor.m_Parameters.m_DataLayout = layout.GetDataLayout(); + descriptor.m_Parameters.m_DataLayout = layout; armnn::WorkloadInfo info; AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); @@ -4729,7 +4729,7 @@ LayerTestResult PadFloat324dTest( LayerTestResult L2Normalization1dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Width: 1 // Height: 1 @@ -4799,7 +4799,7 @@ LayerTestResult L2Normalization1dTest( LayerTestResult L2Normalization2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Width: 5 // Height: 1 @@ -4844,7 +4844,7 @@ LayerTestResult L2Normalization2dTest( LayerTestResult L2Normalization3dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Width: 3 // Height: 4 @@ -4909,7 +4909,7 @@ LayerTestResult L2Normalization3dTest( LayerTestResult L2Normalization4dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout) + const armnn::DataLayout layout) { // Width: 3 // Height: 4 @@ -6357,7 +6357,7 @@ LayerTestResult SimpleMaxPooling2dSize3x3Stride2x4Uint8Test( LayerTestResult SimpleMaxPooling2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { return SimpleMaxPooling2dTestCommon(workloadFactory, memoryManager, dataLayout); } @@ -6365,7 +6365,7 @@ LayerTestResult SimpleMaxPooling2dTest( LayerTestResult SimpleMaxPooling2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { return SimpleMaxPooling2dTestCommon(workloadFactory, memoryManager, dataLayout); } @@ -6373,7 +6373,7 @@ LayerTestResult SimpleMaxPooling2dUint8Test( LayerTestResult SimpleAveragePooling2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { return SimpleAveragePooling2dTestCommon(workloadFactory, memoryManager, dataLayout); } @@ -6381,7 +6381,7 @@ LayerTestResult SimpleAveragePooling2dTest( LayerTestResult SimpleAveragePooling2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { return SimpleAveragePooling2dTestCommon( workloadFactory, memoryManager, dataLayout, 0.5, -1); @@ -6413,7 +6413,7 @@ LayerTestResult LargeTensorsAveragePooling2dUint8Test( LayerTestResult SimpleL2Pooling2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { return SimpleL2Pooling2dTestCommon(workloadFactory, memoryManager, dataLayout); } @@ -6421,7 +6421,7 @@ LayerTestResult SimpleL2Pooling2dTest( LayerTestResult SimpleL2Pooling2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { return SimpleL2Pooling2dTestCommon(workloadFactory, memoryManager, dataLayout); } diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp index 15d0853006..498cfb7fe0 100644 --- a/src/backends/backendsCommon/test/LayerTests.hpp +++ b/src/backends/backendsCommon/test/LayerTests.hpp @@ -58,13 +58,13 @@ LayerTestResult SimpleConvolution2d3x5Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult SimpleConvolution2d3x3Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult SimpleConvolution2d3x3NhwcTest( armnn::IWorkloadFactory& workloadFactory, @@ -75,12 +75,12 @@ LayerTestResult Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult Convolution2dAsymmetricPaddingTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult Convolution1dTest( armnn::IWorkloadFactory& workloadFactory, @@ -96,7 +96,7 @@ LayerTestResult DepthwiseConvolution2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult DepthwiseConvolution2dDepthNhwcTest( armnn::IWorkloadFactory& workloadFactory, @@ -107,13 +107,13 @@ LayerTestResult DepthwiseConvolution2dDepthMul1Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult DepthwiseConvolution2dAsymmetricTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult SimpleMaxPooling2dSize2x2Stride2x2Test( armnn::IWorkloadFactory& workloadFactory, @@ -154,22 +154,22 @@ LayerTestResult IgnorePaddingMaxPooling2dSize3Uint8Test( LayerTestResult SimpleMaxPooling2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult SimpleMaxPooling2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult SimpleAveragePooling2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult SimpleAveragePooling2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult IgnorePaddingAveragePooling2dSize3x2Stride2x2Test( armnn::IWorkloadFactory& workloadFactory, @@ -203,12 +203,12 @@ LayerTestResult IgnorePaddingAveragePooling2dSize3Uint8Test( LayerTestResult SimpleL2Pooling2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult SimpleL2Pooling2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult L2Pooling2dSize3Stride1Test( armnn::IWorkloadFactory& workloadFactory, @@ -464,7 +464,7 @@ LayerTestResult CompareDepthwiseConvolution2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, armnn::IWorkloadFactory& refWorkloadFactory, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult CompareNormalizationTest( armnn::IWorkloadFactory& workloadFactory, @@ -606,32 +606,32 @@ LayerTestResult CompareBoundedReLuTest( LayerTestResult ResizeBilinearNopTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); // Tests the behaviour of the resize bilinear operation when rescaling a 2x2 image into a 1x1 image. LayerTestResult SimpleResizeBilinearTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); // Tests the resize bilinear for minification of a square input matrix (also: input dimensions are a // multiple of output dimensions). LayerTestResult ResizeBilinearSqMinTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); // Tests the resize bilinear for minification (output dimensions smaller than input dimensions). LayerTestResult ResizeBilinearMinTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); // Tests the resize bilinear for magnification (output dimensions bigger than input dimensions). LayerTestResult ResizeBilinearMagTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout); + const armnn::DataLayout dataLayout); LayerTestResult BatchNormTest( armnn::IWorkloadFactory& workloadFactory, @@ -648,22 +648,22 @@ LayerTestResult FakeQuantizationTest( LayerTestResult L2Normalization1dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult L2Normalization2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult L2Normalization3dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult L2Normalization4dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult ConstantTest( armnn::IWorkloadFactory& workloadFactory, @@ -765,25 +765,25 @@ LayerTestResult SimpleConvolution2d3x5Uint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult SimpleConvolution2d3x3Uint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult DepthwiseConvolution2dUint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult DepthwiseConvolution2dDepthMul1Uint8Test( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, bool biasEnabled, - const armnn::DataLayoutIndexed& layout); + const armnn::DataLayout layout); LayerTestResult ConstantLinearActivationUint8Test( armnn::IWorkloadFactory& workloadFactory, diff --git a/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp b/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp index 2e851faaa7..9050fc64a6 100644 --- a/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp +++ b/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp @@ -34,10 +34,11 @@ LayerTestResult SimplePooling2dTestImpl( const boost::multi_array& input, const boost::multi_array& outputExpected) { - const armnn::DataLayoutIndexed dataLayout = descriptor.m_DataLayout; - auto heightIndex = dataLayout.GetHeightIndex(); - auto widthIndex = dataLayout.GetWidthIndex(); - auto channelsIndex = dataLayout.GetChannelsIndex(); + const armnn::DataLayout dataLayout = descriptor.m_DataLayout; + const armnn::DataLayoutIndexed dimensionIndices = dataLayout; + auto heightIndex = dimensionIndices.GetHeightIndex(); + auto widthIndex = dimensionIndices.GetWidthIndex(); + auto channelsIndex = dimensionIndices.GetChannelsIndex(); unsigned int inputHeight = boost::numeric_cast(input.shape()[heightIndex]); unsigned int inputWidth = boost::numeric_cast(input.shape()[widthIndex]); @@ -240,7 +241,7 @@ template LayerTestResult SimpleMaxPooling2dTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::DataLayoutIndexed& dataLayout = armnn::DataLayout::NCHW, + const armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, float qScale = 1.0f, int32_t qOffset = 0) { @@ -286,7 +287,7 @@ LayerTestResult SimpleMaxPooling2dTestCommon( })); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -309,7 +310,7 @@ template LayerTestResult SimpleAveragePooling2dTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - armnn::DataLayoutIndexed dataLayout = armnn::DataLayout::NCHW, + armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, float qScale = 1.0f, int32_t qOffset = 0) { @@ -355,7 +356,7 @@ LayerTestResult SimpleAveragePooling2dTestCommon( })); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); @@ -429,7 +430,7 @@ template LayerTestResult SimpleL2Pooling2dTestCommon( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - armnn::DataLayoutIndexed dataLayout = armnn::DataLayout::NCHW, + armnn::DataLayout dataLayout = armnn::DataLayout::NCHW, float qScale = 1.0f, int32_t qOffset = 0) { @@ -466,7 +467,7 @@ LayerTestResult SimpleL2Pooling2dTestCommon( })); const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 }; - if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC) + if (dataLayout == armnn::DataLayout::NHWC) { std::vector tmp(inputData.size()); armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data()); -- cgit v1.2.1