diff options
author | Narumol Prangnawarat <narumol.prangnawarat@arm.com> | 2020-04-01 16:51:23 +0100 |
---|---|---|
committer | Narumol Prangnawarat <narumol.prangnawarat@arm.com> | 2020-04-06 09:06:01 +0100 |
commit | ac2770a4bb6461bfbddec928bb6208f26f898f02 (patch) | |
tree | c72f67f648b7aca2f4bccf69b05d185bf5f9ccad /src/backends | |
parent | 7ee5d2c3b3cee5a924ed6347fef613ee07b5aca7 (diff) | |
download | armnn-ac2770a4bb6461bfbddec928bb6208f26f898f02.tar.gz |
IVGCVSW-4485 Remove Boost assert
* Change boost assert to armnn assert
* Change include file to armnn assert
* Fix ARMNN_ASSERT_MSG issue with multiple conditions
* Change BOOST_ASSERT to BOOST_TEST where appropriate
* Remove unused include statements
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I5d0fa3a37b7c1c921216de68f0073aa34702c9ff
Diffstat (limited to 'src/backends')
63 files changed, 193 insertions, 197 deletions
diff --git a/src/backends/aclCommon/ArmComputeTensorUtils.cpp b/src/backends/aclCommon/ArmComputeTensorUtils.cpp index f5a9e05de9..7a75f9c872 100644 --- a/src/backends/aclCommon/ArmComputeTensorUtils.cpp +++ b/src/backends/aclCommon/ArmComputeTensorUtils.cpp @@ -42,7 +42,7 @@ arm_compute::DataType GetArmComputeDataType(armnn::DataType dataType, bool multi case armnn::DataType::Signed32: return arm_compute::DataType::S32; default: - BOOST_ASSERT_MSG(false, "Unknown data type"); + ARMNN_ASSERT_MSG(false, "Unknown data type"); return arm_compute::DataType::UNKNOWN; } } diff --git a/src/backends/aclCommon/ArmComputeUtils.hpp b/src/backends/aclCommon/ArmComputeUtils.hpp index 9c6f46462e..80bb7623e8 100644 --- a/src/backends/aclCommon/ArmComputeUtils.hpp +++ b/src/backends/aclCommon/ArmComputeUtils.hpp @@ -6,11 +6,10 @@ #include <armnn/Descriptors.hpp> #include <armnn/Tensor.hpp> +#include <armnn/utility/Assert.hpp> #include <arm_compute/core/Types.h> -#include <boost/assert.hpp> - namespace armnn { @@ -161,7 +160,7 @@ inline unsigned int ComputeSoftmaxAclAxis(const SoftmaxDescriptor& softmaxDesc, unsigned int dim = tensor.GetNumDimensions(); - BOOST_ASSERT(dim != 0); + ARMNN_ASSERT(dim != 0); // Currently ArmNN support axis 1. return dim - 1; diff --git a/src/backends/aclCommon/BaseMemoryManager.cpp b/src/backends/aclCommon/BaseMemoryManager.cpp index 844fbcd4ca..b43eaf8da3 100644 --- a/src/backends/aclCommon/BaseMemoryManager.cpp +++ b/src/backends/aclCommon/BaseMemoryManager.cpp @@ -19,7 +19,7 @@ namespace armnn BaseMemoryManager::BaseMemoryManager(std::unique_ptr<arm_compute::IAllocator> alloc, MemoryAffinity memoryAffinity) { - BOOST_ASSERT(alloc); + ARMNN_ASSERT(alloc); m_Allocator = std::move(alloc); m_IntraLayerMemoryMgr = CreateArmComputeMemoryManager(memoryAffinity); @@ -51,30 +51,30 @@ void BaseMemoryManager::Acquire() static const size_t s_NumPools = 1; // Allocate memory pools for intra-layer memory manager - BOOST_ASSERT(m_IntraLayerMemoryMgr); + ARMNN_ASSERT(m_IntraLayerMemoryMgr); m_IntraLayerMemoryMgr->populate(*m_Allocator, s_NumPools); // Allocate memory pools for inter-layer memory manager - BOOST_ASSERT(m_InterLayerMemoryMgr); + ARMNN_ASSERT(m_InterLayerMemoryMgr); m_InterLayerMemoryMgr->populate(*m_Allocator, s_NumPools); // Acquire inter-layer memory group. NOTE: This has to come after allocating the pools - BOOST_ASSERT(m_InterLayerMemoryGroup); + ARMNN_ASSERT(m_InterLayerMemoryGroup); m_InterLayerMemoryGroup->acquire(); } void BaseMemoryManager::Release() { // Release inter-layer memory group. NOTE: This has to come before releasing the pools - BOOST_ASSERT(m_InterLayerMemoryGroup); + ARMNN_ASSERT(m_InterLayerMemoryGroup); m_InterLayerMemoryGroup->release(); // Release memory pools managed by intra-layer memory manager - BOOST_ASSERT(m_IntraLayerMemoryMgr); + ARMNN_ASSERT(m_IntraLayerMemoryMgr); m_IntraLayerMemoryMgr->clear(); // Release memory pools managed by inter-layer memory manager - BOOST_ASSERT(m_InterLayerMemoryMgr); + ARMNN_ASSERT(m_InterLayerMemoryMgr); m_InterLayerMemoryMgr->clear(); } #else diff --git a/src/backends/backendsCommon/CpuTensorHandle.cpp b/src/backends/backendsCommon/CpuTensorHandle.cpp index 65e6c47179..7bcf59fdf1 100644 --- a/src/backends/backendsCommon/CpuTensorHandle.cpp +++ b/src/backends/backendsCommon/CpuTensorHandle.cpp @@ -118,8 +118,8 @@ void ScopedCpuTensorHandle::CopyFrom(const ScopedCpuTensorHandle& other) void ScopedCpuTensorHandle::CopyFrom(const void* srcMemory, unsigned int numBytes) { - BOOST_ASSERT(GetTensor<void>() == nullptr); - BOOST_ASSERT(GetTensorInfo().GetNumBytes() == numBytes); + ARMNN_ASSERT(GetTensor<void>() == nullptr); + ARMNN_ASSERT(GetTensorInfo().GetNumBytes() == numBytes); if (srcMemory) { diff --git a/src/backends/backendsCommon/CpuTensorHandle.hpp b/src/backends/backendsCommon/CpuTensorHandle.hpp index e6e59fcd4f..78efb08f99 100644 --- a/src/backends/backendsCommon/CpuTensorHandle.hpp +++ b/src/backends/backendsCommon/CpuTensorHandle.hpp @@ -14,7 +14,7 @@ #include <algorithm> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> namespace armnn { @@ -30,7 +30,7 @@ public: template <typename T> const T* GetConstTensor() const { - BOOST_ASSERT(CompatibleTypes<T>(GetTensorInfo().GetDataType())); + ARMNN_ASSERT(CompatibleTypes<T>(GetTensorInfo().GetDataType())); return reinterpret_cast<const T*>(m_Memory); } @@ -59,8 +59,8 @@ protected: private: // Only used for testing - void CopyOutTo(void *) const override { BOOST_ASSERT_MSG(false, "Unimplemented"); } - void CopyInFrom(const void*) override { BOOST_ASSERT_MSG(false, "Unimplemented"); } + void CopyOutTo(void *) const override { ARMNN_ASSERT_MSG(false, "Unimplemented"); } + void CopyInFrom(const void*) override { ARMNN_ASSERT_MSG(false, "Unimplemented"); } ConstCpuTensorHandle(const ConstCpuTensorHandle& other) = delete; ConstCpuTensorHandle& operator=(const ConstCpuTensorHandle& other) = delete; @@ -79,7 +79,7 @@ public: template <typename T> T* GetTensor() const { - BOOST_ASSERT(CompatibleTypes<T>(GetTensorInfo().GetDataType())); + ARMNN_ASSERT(CompatibleTypes<T>(GetTensorInfo().GetDataType())); return reinterpret_cast<T*>(m_MutableMemory); } diff --git a/src/backends/backendsCommon/LayerSupportRules.hpp b/src/backends/backendsCommon/LayerSupportRules.hpp index 03bec53353..ddecc82172 100644 --- a/src/backends/backendsCommon/LayerSupportRules.hpp +++ b/src/backends/backendsCommon/LayerSupportRules.hpp @@ -5,7 +5,7 @@ #pragma once -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> #include <algorithm> namespace armnn @@ -30,7 +30,7 @@ inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Option case armnn::DataType::QAsymmS8: return armnn::DataType::Signed32; default: - BOOST_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type."); + ARMNN_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type."); } return armnn::EmptyOptional(); } diff --git a/src/backends/backendsCommon/MakeWorkloadHelper.hpp b/src/backends/backendsCommon/MakeWorkloadHelper.hpp index 8abc8a6ef5..560182286e 100644 --- a/src/backends/backendsCommon/MakeWorkloadHelper.hpp +++ b/src/backends/backendsCommon/MakeWorkloadHelper.hpp @@ -70,7 +70,7 @@ std::unique_ptr<IWorkload> MakeWorkloadHelper(const QueueDescriptorType& descrip case DataType::QSymmS16: return nullptr; default: - BOOST_ASSERT_MSG(false, "Unknown DataType."); + ARMNN_ASSERT_MSG(false, "Unknown DataType."); return nullptr; } } diff --git a/src/backends/backendsCommon/Workload.hpp b/src/backends/backendsCommon/Workload.hpp index 984443b79b..244b5f1249 100644 --- a/src/backends/backendsCommon/Workload.hpp +++ b/src/backends/backendsCommon/Workload.hpp @@ -65,9 +65,9 @@ public: if (std::find(dataTypes.begin(), dataTypes.end(), expectedInputType) == dataTypes.end()) { - BOOST_ASSERT_MSG(false, "Trying to create workload with incorrect type"); + ARMNN_ASSERT_MSG(false, "Trying to create workload with incorrect type"); } - BOOST_ASSERT_MSG(std::all_of(std::next(info.m_InputTensorInfos.begin()), + ARMNN_ASSERT_MSG(std::all_of(std::next(info.m_InputTensorInfos.begin()), info.m_InputTensorInfos.end(), [&](auto it){ return it.GetDataType() == expectedInputType; @@ -84,14 +84,14 @@ public: { if (expectedOutputType != expectedInputType) { - BOOST_ASSERT_MSG(false, "Trying to create workload with incorrect type"); + ARMNN_ASSERT_MSG(false, "Trying to create workload with incorrect type"); } } else if (std::find(dataTypes.begin(), dataTypes.end(), expectedOutputType) == dataTypes.end()) { - BOOST_ASSERT_MSG(false, "Trying to create workload with incorrect type"); + ARMNN_ASSERT_MSG(false, "Trying to create workload with incorrect type"); } - BOOST_ASSERT_MSG(std::all_of(std::next(info.m_OutputTensorInfos.begin()), + ARMNN_ASSERT_MSG(std::all_of(std::next(info.m_OutputTensorInfos.begin()), info.m_OutputTensorInfos.end(), [&](auto it){ return it.GetDataType() == expectedOutputType; @@ -109,14 +109,14 @@ public: MultiTypedWorkload(const QueueDescriptor& descriptor, const WorkloadInfo& info) : BaseWorkload<QueueDescriptor>(descriptor, info) { - BOOST_ASSERT_MSG(std::all_of(info.m_InputTensorInfos.begin(), + ARMNN_ASSERT_MSG(std::all_of(info.m_InputTensorInfos.begin(), info.m_InputTensorInfos.end(), [&](auto it){ return it.GetDataType() == InputDataType; }), "Trying to create workload with incorrect type"); - BOOST_ASSERT_MSG(std::all_of(info.m_OutputTensorInfos.begin(), + ARMNN_ASSERT_MSG(std::all_of(info.m_OutputTensorInfos.begin(), info.m_OutputTensorInfos.end(), [&](auto it){ return it.GetDataType() == OutputDataType; @@ -136,11 +136,11 @@ public: { if (!info.m_InputTensorInfos.empty()) { - BOOST_ASSERT_MSG(info.m_InputTensorInfos.front().GetDataType() == DataType, + ARMNN_ASSERT_MSG(info.m_InputTensorInfos.front().GetDataType() == DataType, "Trying to create workload with incorrect type"); } - BOOST_ASSERT_MSG(std::all_of(info.m_OutputTensorInfos.begin(), + ARMNN_ASSERT_MSG(std::all_of(info.m_OutputTensorInfos.begin(), info.m_OutputTensorInfos.end(), [&](auto it){ return it.GetDataType() == DataType; diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp index f968ad78f7..1f4a849ee9 100644 --- a/src/backends/backendsCommon/WorkloadData.cpp +++ b/src/backends/backendsCommon/WorkloadData.cpp @@ -40,7 +40,7 @@ DataType GetBiasDataType(DataType inputDataType) case DataType::QSymmS16: return DataType::Signed32; default: - BOOST_ASSERT_MSG(false, "Invalid input data type"); + ARMNN_ASSERT_MSG(false, "Invalid input data type"); return DataType::Float32; } } diff --git a/src/backends/backendsCommon/WorkloadFactory.cpp b/src/backends/backendsCommon/WorkloadFactory.cpp index 5628c36884..a7e8576668 100644 --- a/src/backends/backendsCommon/WorkloadFactory.cpp +++ b/src/backends/backendsCommon/WorkloadFactory.cpp @@ -194,7 +194,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), dataType); const TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); - BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); + ARMNN_ASSERT(cLayer->m_Weight.get() != nullptr); const Convolution2dDescriptor& descriptor = cLayer->GetParameters(); @@ -244,7 +244,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, const TensorInfo& input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), dataType); const TensorInfo& output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); - BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); + ARMNN_ASSERT(cLayer->m_Weight.get() != nullptr); const DepthwiseConvolution2dDescriptor& descriptor = cLayer->GetParameters(); @@ -335,7 +335,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, auto cLayer = boost::polymorphic_downcast<const FullyConnectedLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); - BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); + ARMNN_ASSERT(cLayer->m_Weight.get() != nullptr); TensorInfo biasInfo; const TensorInfo * biasInfoPtr = nullptr; @@ -347,7 +347,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, const FullyConnectedDescriptor& descriptor = cLayer->GetParameters(); if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(cLayer->m_Bias.get() != nullptr); + ARMNN_ASSERT(cLayer->m_Bias.get() != nullptr); biasInfo = OverrideDataType(cLayer->m_Bias->GetTensorInfo(), GetBiasTypeFromWeightsType(dataType)); biasInfoPtr = &biasInfo; } @@ -381,7 +381,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } default: { - BOOST_ASSERT_MSG(false, "Unexpected bias type"); + ARMNN_ASSERT_MSG(false, "Unexpected bias type"); } } } @@ -1156,12 +1156,12 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, Optional<TensorInfo> biases; if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(cLayer->m_Bias.get() != nullptr); + ARMNN_ASSERT(cLayer->m_Bias.get() != nullptr); biases = OverrideDataType(cLayer->m_Bias->GetTensorInfo(), GetBiasTypeFromWeightsType(dataType)); } - BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); + ARMNN_ASSERT(cLayer->m_Weight.get() != nullptr); const TensorInfo weights = OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType); result = layerSupportObject->IsTransposeConvolution2dSupported(input, @@ -1175,7 +1175,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } default: { - BOOST_ASSERT_MSG(false, "WorkloadFactory did not recognise type of layer."); + ARMNN_ASSERT_MSG(false, "WorkloadFactory did not recognise type of layer."); reason.value() = "Unrecognised layer type"; result = false; break; diff --git a/src/backends/backendsCommon/WorkloadUtils.cpp b/src/backends/backendsCommon/WorkloadUtils.cpp index 3b3959ba9f..bd5e81e678 100644 --- a/src/backends/backendsCommon/WorkloadUtils.cpp +++ b/src/backends/backendsCommon/WorkloadUtils.cpp @@ -13,8 +13,8 @@ namespace armnn armnn::ConstTensor PermuteTensor(const ConstCpuTensorHandle* tensor, const PermutationVector& permutationVector, void* permuteBuffer) { - BOOST_ASSERT_MSG(tensor, "Invalid input tensor"); - BOOST_ASSERT_MSG(permuteBuffer, "Invalid permute buffer"); + ARMNN_ASSERT_MSG(tensor, "Invalid input tensor"); + ARMNN_ASSERT_MSG(permuteBuffer, "Invalid permute buffer"); TensorInfo tensorInfo = tensor->GetTensorInfo(); @@ -133,8 +133,8 @@ armnn::ConstTensor ConvertWeightTensorFromArmnnToAcl(const ConstCpuTensorHandle* DataLayout dataLayout, void* permuteBuffer) { - BOOST_ASSERT_MSG(weightTensor, "Invalid input tensor"); - BOOST_ASSERT_MSG(permuteBuffer, "Invalid permute buffer"); + ARMNN_ASSERT_MSG(weightTensor, "Invalid input tensor"); + ARMNN_ASSERT_MSG(permuteBuffer, "Invalid permute buffer"); auto multiplier = weightTensor->GetTensorInfo().GetShape()[0]; auto inputChannels = weightTensor->GetTensorInfo().GetShape()[1]; diff --git a/src/backends/backendsCommon/WorkloadUtils.hpp b/src/backends/backendsCommon/WorkloadUtils.hpp index 66056db4ca..a4da924725 100644 --- a/src/backends/backendsCommon/WorkloadUtils.hpp +++ b/src/backends/backendsCommon/WorkloadUtils.hpp @@ -168,8 +168,8 @@ void CopyTensorContentsGeneric(const ITensorHandle* srcTensor, ITensorHandle* ds auto dstPtrChannel = dstData; for (unsigned int w = 0; w < copyWidth; ++w) { - BOOST_ASSERT(srcData >= srcDataStart && srcData + copyLength <= srcDataStart + srcSize); - BOOST_ASSERT(dstData >= dstDataStart && dstData + copyLength <= dstDataStart + dstSize); + ARMNN_ASSERT(srcData >= srcDataStart && srcData + copyLength <= srcDataStart + srcSize); + ARMNN_ASSERT(dstData >= dstDataStart && dstData + copyLength <= dstDataStart + dstSize); copy(dstData, srcData, copyLength); dstData += dstWidthStride; srcData += srcWidthStride; diff --git a/src/backends/backendsCommon/test/MockBackend.cpp b/src/backends/backendsCommon/test/MockBackend.cpp index 116bf77c63..abdaa8131b 100644 --- a/src/backends/backendsCommon/test/MockBackend.cpp +++ b/src/backends/backendsCommon/test/MockBackend.cpp @@ -23,7 +23,7 @@ namespace bool IsLayerSupported(const armnn::Layer* layer) { - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); armnn::LayerType layerType = layer->GetType(); switch (layerType) @@ -47,7 +47,7 @@ bool IsLayerSupported(const armnn::Layer& layer) bool IsLayerOptimizable(const armnn::Layer* layer) { - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); // A Layer is not optimizable if its name contains "unoptimizable" const std::string layerName(layer->GetName()); @@ -191,7 +191,7 @@ OptimizationViews MockBackend::OptimizeSubgraphView(const SubgraphView& subgraph supportedSubgraphs.end(), [&optimizationViews](const SubgraphView::SubgraphViewPtr& supportedSubgraph) { - BOOST_ASSERT(supportedSubgraph != nullptr); + ARMNN_ASSERT(supportedSubgraph != nullptr); PreCompiledLayer* preCompiledLayer = optimizationViews.GetGraph().AddLayer<PreCompiledLayer>( @@ -228,7 +228,7 @@ OptimizationViews MockBackend::OptimizeSubgraphView(const SubgraphView& subgraph unsupportedSubgraphs.end(), [&optimizationViews](const SubgraphView::SubgraphViewPtr& unsupportedSubgraph) { - BOOST_ASSERT(unsupportedSubgraph != nullptr); + ARMNN_ASSERT(unsupportedSubgraph != nullptr); optimizationViews.AddFailedSubgraph(SubgraphView(*unsupportedSubgraph)); }); @@ -256,7 +256,7 @@ OptimizationViews MockBackend::OptimizeSubgraphView(const SubgraphView& subgraph untouchedSubgraphs.end(), [&optimizationViews](const SubgraphView::SubgraphViewPtr& untouchedSubgraph) { - BOOST_ASSERT(untouchedSubgraph != nullptr); + ARMNN_ASSERT(untouchedSubgraph != nullptr); optimizationViews.AddUntouchedSubgraph(SubgraphView(*untouchedSubgraph)); }); diff --git a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp index df001b7530..9f38e47715 100644 --- a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp +++ b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp @@ -106,7 +106,7 @@ inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Option case armnn::DataType::QSymmS16: return armnn::DataType::Signed32; default: - BOOST_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type."); + ARMNN_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type."); } return armnn::EmptyOptional(); } diff --git a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp index 319434e093..a82048cd81 100644 --- a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp @@ -1212,9 +1212,9 @@ LayerTestResult<T,4> CompareActivationTestImpl( SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get()); std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateActivation(data, info); - BOOST_ASSERT(workload != nullptr); + ARMNN_ASSERT(workload != nullptr); std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.CreateActivation(refData, refInfo); - BOOST_ASSERT(workloadRef != nullptr); + ARMNN_ASSERT(workloadRef != nullptr); inputHandle->Allocate(); outputHandle->Allocate(); diff --git a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp index 2156b0ee9e..a6b703b08b 100644 --- a/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/ComparisonTestImpl.cpp @@ -5,7 +5,7 @@ #include "ComparisonTestImpl.hpp" - +#include <armnn/utility/Assert.hpp> #include <Half.hpp> #include <QuantizeHelper.hpp> #include <ResolveType.hpp> @@ -18,8 +18,6 @@ #include <test/TensorHelpers.hpp> -#include <boost/assert.hpp> - namespace { @@ -44,13 +42,13 @@ LayerTestResult<uint8_t, NumDims> ComparisonTestImpl( int outQuantOffset) { IgnoreUnused(memoryManager); - BOOST_ASSERT(shape0.GetNumDimensions() == NumDims); + ARMNN_ASSERT(shape0.GetNumDimensions() == NumDims); armnn::TensorInfo inputTensorInfo0(shape0, ArmnnInType, quantScale0, quantOffset0); - BOOST_ASSERT(shape1.GetNumDimensions() == NumDims); + ARMNN_ASSERT(shape1.GetNumDimensions() == NumDims); armnn::TensorInfo inputTensorInfo1(shape1, ArmnnInType, quantScale1, quantOffset1); - BOOST_ASSERT(outShape.GetNumDimensions() == NumDims); + ARMNN_ASSERT(outShape.GetNumDimensions() == NumDims); armnn::TensorInfo outputTensorInfo(outShape, armnn::DataType::Boolean, outQuantScale, outQuantOffset); auto input0 = MakeTensor<InType, NumDims>(inputTensorInfo0, values0); diff --git a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp index 1e40b42dcf..9e08e30dec 100644 --- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp @@ -61,7 +61,7 @@ bool NeedPermuteForConcat( } else { - BOOST_ASSERT_MSG(nDimensions == tensorInfo.GetShape().GetNumDimensions(), + ARMNN_ASSERT_MSG(nDimensions == tensorInfo.GetShape().GetNumDimensions(), "Input shapes must have the same number of dimensions"); } } @@ -92,7 +92,7 @@ void Generate3dPermuteVectorForConcat( unsigned int & concatDim, std::pair<PermutationVector, PermutationVector> & permutations) { - BOOST_ASSERT_MSG(numDimensions <= 3, + ARMNN_ASSERT_MSG(numDimensions <= 3, "Only dimensions 1,2 and 3 are supported by this helper"); unsigned int expandedBy = 3 - numDimensions; unsigned int expandedConcatAxis = concatDim + expandedBy; @@ -113,7 +113,7 @@ void Generate3dPermuteVectorForConcat( } else { - BOOST_ASSERT(expandedConcatAxis == 0); + ARMNN_ASSERT(expandedConcatAxis == 0); concatDim = 0; } } @@ -127,7 +127,7 @@ template<typename T> void PermuteTensorData( std::vector<T>& outputData) { IgnoreUnused(memoryManager); - BOOST_ASSERT_MSG(inputData != nullptr, "inputData must not be null"); + ARMNN_ASSERT_MSG(inputData != nullptr, "inputData must not be null"); if (inputData == nullptr) { // Nullptr is an error in the test. By returning without doing the concatenation @@ -179,7 +179,7 @@ template<typename T> void PermuteInputsForConcat( TensorInfo & outputTensorInfo) { IgnoreUnused(memoryManager); - BOOST_ASSERT_MSG(inputTensorInfos.size() > 1, + ARMNN_ASSERT_MSG(inputTensorInfos.size() > 1, "Expecting more than one tensor to be concatenated here"); unsigned int numDims = 0; @@ -200,12 +200,12 @@ template<typename T> void PermuteInputsForConcat( // Store the reverese permutation. permuteVector = permutations.second; - BOOST_ASSERT_MSG(!permuteVector.IsEqual(identity), + ARMNN_ASSERT_MSG(!permuteVector.IsEqual(identity), "Test logic error, we don't need permutation, so we shouldn't arrive here"); } else { - BOOST_ASSERT_MSG(numDims == tensorInfo.GetShape().GetNumDimensions(), + ARMNN_ASSERT_MSG(numDims == tensorInfo.GetShape().GetNumDimensions(), "All inputs must have the same number of dimensions"); } @@ -244,7 +244,7 @@ template <typename T> void PermuteOutputForConcat( std::unique_ptr<ITensorHandle> && inputDataHandle, T * data) { - BOOST_ASSERT_MSG(data != nullptr, "data must not be null"); + ARMNN_ASSERT_MSG(data != nullptr, "data must not be null"); if (data == nullptr) { // Nullptr is an error in the test. By returning without doing the permutation @@ -279,7 +279,7 @@ template<typename T> void Concatenate( unsigned int concatDim, bool useSubtensor) { - BOOST_ASSERT_MSG(output != nullptr, "output must not be null"); + ARMNN_ASSERT_MSG(output != nullptr, "output must not be null"); if (output == nullptr) { // Nullptr is an error in the test. By returning without doing the permutation diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp index 50ad667dde..c66027efdf 100644 --- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp @@ -169,9 +169,9 @@ template<typename T, typename B> void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset, const std::vector<B>& bias, float bScale, int32_t bOffset, uint32_t w, uint32_t h) { - BOOST_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()), + ARMNN_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()), "Invalid type and parameter combination."); - BOOST_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()), + ARMNN_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()), "Invalid type and parameter combination."); // Note we need to dequantize and re-quantize the image value and the bias. @@ -183,7 +183,7 @@ void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset, for (uint32_t x = 0; x < w; ++x) { uint32_t offset = (i * h + y) * w + x; - BOOST_ASSERT(offset < v.size()); + ARMNN_ASSERT(offset < v.size()); T& outRef = v[offset]; float dOutput = SelectiveDequantize(outRef, vScale, vOffset); outRef = SelectiveQuantize<T>(dOutput + dBias, vScale, vOffset); @@ -236,11 +236,11 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl( bool biasEnabled = bias.size() > 0; // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches). - BOOST_ASSERT(inputNum == 1); - BOOST_ASSERT(outputNum == 1); + ARMNN_ASSERT(inputNum == 1); + ARMNN_ASSERT(outputNum == 1); // If a bias is used, its size must equal the number of output channels. - BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels); + ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); // Note these tensors will use two (identical) batches. @@ -1627,7 +1627,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl( // If a bias is used, its size must equal the number of output channels. bool biasEnabled = bias.size() > 0; - BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels); + ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); // Creates the tensors. armnn::TensorInfo inputTensorInfo = @@ -2135,11 +2135,11 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( bool biasEnabled = bias.size() > 0; // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches). - BOOST_ASSERT(inputNum == 1); - BOOST_ASSERT(outputNum == 1); + ARMNN_ASSERT(inputNum == 1); + ARMNN_ASSERT(outputNum == 1); // If a bias is used, its size must equal the number of output channels. - BOOST_ASSERT(!biasEnabled || bias.size() == outputChannels); + ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); // Note these tensors will use two (identical) batches. diff --git a/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp b/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp index c277d2d5e1..c64fc88024 100644 --- a/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp +++ b/src/backends/backendsCommon/test/layerTests/LayerTestResult.hpp @@ -6,6 +6,7 @@ #pragma once #include <armnn/Tensor.hpp> +#include <armnn/utility/Assert.hpp> #include <boost/multi_array.hpp> @@ -14,7 +15,7 @@ template <std::size_t n> boost::array<unsigned int, n> GetTensorShapeAsArray(const armnn::TensorInfo& tensorInfo) { - BOOST_ASSERT_MSG(n == tensorInfo.GetNumDimensions(), + ARMNN_ASSERT_MSG(n == tensorInfo.GetNumDimensions(), "Attempting to construct a shape array of mismatching size"); boost::array<unsigned int, n> shape; diff --git a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp index 772ae2ccc7..953b543acb 100644 --- a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp @@ -104,7 +104,7 @@ LayerTestResult<T, n> SimpleSoftmaxBaseTestImpl( outputHandle->Allocate(); CopyDataToITensorHandle(inputHandle.get(), input.origin()); - BOOST_ASSERT(workload); + ARMNN_ASSERT(workload); ExecuteWorkload(*workload, memoryManager); diff --git a/src/backends/cl/ClBackendContext.cpp b/src/backends/cl/ClBackendContext.cpp index 068e2958af..f612c3743d 100644 --- a/src/backends/cl/ClBackendContext.cpp +++ b/src/backends/cl/ClBackendContext.cpp @@ -7,6 +7,7 @@ #include "ClContextControl.hpp" #include <armnn/Logging.hpp> +#include <armnn/utility/Assert.hpp> #include <arm_compute/core/CL/OpenCL.h> #include <arm_compute/core/CL/CLKernelLibrary.h> @@ -184,7 +185,7 @@ ClBackendContext::ClBackendContext(const IRuntime::CreationOptions& options) return TuningLevel::Exhaustive; default: { - BOOST_ASSERT_MSG(false, "Tuning level not recognised."); + ARMNN_ASSERT_MSG(false, "Tuning level not recognised."); return TuningLevel::None; } } diff --git a/src/backends/cl/ClContextControl.cpp b/src/backends/cl/ClContextControl.cpp index f307133085..dbcccce945 100644 --- a/src/backends/cl/ClContextControl.cpp +++ b/src/backends/cl/ClContextControl.cpp @@ -9,12 +9,12 @@ #include <LeakChecking.hpp> +#include <armnn/utility/Assert.hpp> #include <armnn/utility/IgnoreUnused.hpp> #include <arm_compute/core/CL/CLKernelLibrary.h> #include <arm_compute/runtime/CL/CLScheduler.h> -#include <boost/assert.hpp> #include <boost/format.hpp> #include <boost/polymorphic_cast.hpp> @@ -59,11 +59,11 @@ ClContextControl::ClContextControl(arm_compute::CLTuner *tuner, // Removes the use of global CL context. cl::Context::setDefault(cl::Context{}); - BOOST_ASSERT(cl::Context::getDefault()() == NULL); + ARMNN_ASSERT(cl::Context::getDefault()() == NULL); // Removes the use of global CL command queue. cl::CommandQueue::setDefault(cl::CommandQueue{}); - BOOST_ASSERT(cl::CommandQueue::getDefault()() == NULL); + ARMNN_ASSERT(cl::CommandQueue::getDefault()() == NULL); // Always load the OpenCL runtime. LoadOpenClRuntime(); diff --git a/src/backends/cl/workloads/ClConstantWorkload.cpp b/src/backends/cl/workloads/ClConstantWorkload.cpp index 39ae14eaf3..e928870324 100644 --- a/src/backends/cl/workloads/ClConstantWorkload.cpp +++ b/src/backends/cl/workloads/ClConstantWorkload.cpp @@ -33,7 +33,7 @@ void ClConstantWorkload::Execute() const { const ConstantQueueDescriptor& data = this->m_Data; - BOOST_ASSERT(data.m_LayerOutput != nullptr); + ARMNN_ASSERT(data.m_LayerOutput != nullptr); arm_compute::CLTensor& output = static_cast<ClTensorHandle*>(data.m_Outputs[0])->GetTensor(); arm_compute::DataType computeDataType = static_cast<ClTensorHandle*>(data.m_Outputs[0])->GetDataType(); @@ -56,7 +56,7 @@ void ClConstantWorkload::Execute() const } default: { - BOOST_ASSERT_MSG(false, "Unknown data type"); + ARMNN_ASSERT_MSG(false, "Unknown data type"); break; } } diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp index e8af0ee3b7..73ec95ce9f 100644 --- a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp +++ b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp @@ -38,7 +38,7 @@ arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input, if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(biases.has_value()); + ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp index 858eab4e00..8704b1276f 100644 --- a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp +++ b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp @@ -45,7 +45,7 @@ arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo& inp if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(biases.has_value()); + ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; @@ -125,7 +125,7 @@ ClDepthwiseConvolutionWorkload::ClDepthwiseConvolutionWorkload( arm_compute::ActivationLayerInfo(), aclDilationInfo); - BOOST_ASSERT(m_DepthwiseConvolutionLayer); + ARMNN_ASSERT(m_DepthwiseConvolutionLayer); ScopedCpuTensorHandle weightsPermutedHandle(weightPermuted); InitializeArmComputeClTensorData(*m_KernelTensor, &weightsPermutedHandle); @@ -148,7 +148,7 @@ void ClDepthwiseConvolutionWorkload::FreeUnusedTensors() void ClDepthwiseConvolutionWorkload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_CL("ClDepthwiseConvolutionWorkload_Execute"); - BOOST_ASSERT(m_DepthwiseConvolutionLayer); + ARMNN_ASSERT(m_DepthwiseConvolutionLayer); RunClFunction(*m_DepthwiseConvolutionLayer, CHECK_LOCATION()); } diff --git a/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp index 7c0736645b..20b2104c62 100644 --- a/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp +++ b/src/backends/cl/workloads/ClTransposeConvolution2dWorkload.cpp @@ -38,7 +38,7 @@ arm_compute::Status ClTransposeConvolution2dWorkloadValidate(const TensorInfo& i if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(biases.has_value()); + ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; diff --git a/src/backends/cl/workloads/ClWorkloadUtils.hpp b/src/backends/cl/workloads/ClWorkloadUtils.hpp index b4bcc1c017..54e7717b7d 100644 --- a/src/backends/cl/workloads/ClWorkloadUtils.hpp +++ b/src/backends/cl/workloads/ClWorkloadUtils.hpp @@ -90,7 +90,7 @@ inline auto SetClSliceData(const std::vector<unsigned int>& m_begin, inline void InitializeArmComputeClTensorData(arm_compute::CLTensor& clTensor, const ConstCpuTensorHandle* handle) { - BOOST_ASSERT(handle); + ARMNN_ASSERT(handle); armcomputetensorutils::InitialiseArmComputeTensorEmpty(clTensor); switch(handle->GetTensorInfo().GetDataType()) @@ -116,7 +116,7 @@ inline void InitializeArmComputeClTensorData(arm_compute::CLTensor& clTensor, CopyArmComputeClTensorData(clTensor, handle->GetConstTensor<int32_t>()); break; default: - BOOST_ASSERT_MSG(false, "Unexpected tensor type."); + ARMNN_ASSERT_MSG(false, "Unexpected tensor type."); } }; diff --git a/src/backends/neon/NeonInterceptorScheduler.cpp b/src/backends/neon/NeonInterceptorScheduler.cpp index d8dd01bd6c..745c5fde62 100644 --- a/src/backends/neon/NeonInterceptorScheduler.cpp +++ b/src/backends/neon/NeonInterceptorScheduler.cpp @@ -5,8 +5,6 @@ #include "NeonInterceptorScheduler.hpp" -#include <boost/assert.hpp> - namespace armnn{ NeonInterceptorScheduler::NeonInterceptorScheduler(arm_compute::IScheduler &realScheduler) diff --git a/src/backends/neon/NeonTensorHandle.hpp b/src/backends/neon/NeonTensorHandle.hpp index 11d20878d7..fb2c2b5128 100644 --- a/src/backends/neon/NeonTensorHandle.hpp +++ b/src/backends/neon/NeonTensorHandle.hpp @@ -7,6 +7,8 @@ #include <BFloat16.hpp> #include <Half.hpp> +#include <armnn/utility/Assert.hpp> + #include <aclCommon/ArmComputeTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> @@ -61,7 +63,7 @@ public: // If we have enabled Importing, don't manage the tensor if (!m_IsImportEnabled) { - BOOST_ASSERT(m_MemoryGroup != nullptr); + ARMNN_ASSERT(m_MemoryGroup != nullptr); m_MemoryGroup->manage(&m_Tensor); } } diff --git a/src/backends/neon/NeonTimer.cpp b/src/backends/neon/NeonTimer.cpp index 219edc9680..1079a0d57c 100644 --- a/src/backends/neon/NeonTimer.cpp +++ b/src/backends/neon/NeonTimer.cpp @@ -6,9 +6,10 @@ #include "NeonTimer.hpp" #include "NeonInterceptorScheduler.hpp" +#include <armnn/utility/Assert.hpp> + #include <memory> -#include <boost/assert.hpp> #include <boost/format.hpp> namespace armnn @@ -21,7 +22,7 @@ static thread_local auto g_Interceptor = std::make_shared<NeonInterceptorSchedul void NeonTimer::Start() { m_Kernels.clear(); - BOOST_ASSERT(g_Interceptor->GetKernels() == nullptr); + ARMNN_ASSERT(g_Interceptor->GetKernels() == nullptr); g_Interceptor->SetKernels(&m_Kernels); m_RealSchedulerType = arm_compute::Scheduler::get_type(); diff --git a/src/backends/neon/workloads/NeonConstantWorkload.cpp b/src/backends/neon/workloads/NeonConstantWorkload.cpp index 83a2692b6e..b9cb807779 100644 --- a/src/backends/neon/workloads/NeonConstantWorkload.cpp +++ b/src/backends/neon/workloads/NeonConstantWorkload.cpp @@ -39,7 +39,7 @@ void NeonConstantWorkload::Execute() const { const ConstantQueueDescriptor& data = this->m_Data; - BOOST_ASSERT(data.m_LayerOutput != nullptr); + ARMNN_ASSERT(data.m_LayerOutput != nullptr); arm_compute::ITensor& output = boost::polymorphic_downcast<NeonTensorHandle*>(data.m_Outputs[0])->GetTensor(); arm_compute::DataType computeDataType = @@ -69,7 +69,7 @@ void NeonConstantWorkload::Execute() const } default: { - BOOST_ASSERT_MSG(false, "Unknown data type"); + ARMNN_ASSERT_MSG(false, "Unknown data type"); break; } } diff --git a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp index 683decd45c..5d45642eef 100644 --- a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp +++ b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp @@ -37,7 +37,7 @@ arm_compute::Status NeonConvolution2dWorkloadValidate(const TensorInfo& input, if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(biases.has_value()); + ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; @@ -97,7 +97,7 @@ NeonConvolution2dWorkload::NeonConvolution2dWorkload( m_ConvolutionLayer.reset(convolutionLayer.release()); - BOOST_ASSERT(m_ConvolutionLayer); + ARMNN_ASSERT(m_ConvolutionLayer); InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight); diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp index e39fe54199..a9a3c75bfd 100644 --- a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp +++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp @@ -49,7 +49,7 @@ arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo& i if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(biases.has_value()); + ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; @@ -127,7 +127,7 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( arm_compute::ActivationLayerInfo(), aclDilationInfo); - BOOST_ASSERT(m_pDepthwiseConvolutionLayer); + ARMNN_ASSERT(m_pDepthwiseConvolutionLayer); ScopedCpuTensorHandle weightsPermutedHandle(weightPermuted); InitializeArmComputeTensorData(*m_KernelTensor, &weightsPermutedHandle); @@ -144,7 +144,7 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( void NeonDepthwiseConvolutionWorkload::Execute() const { ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonDepthwiseConvolutionWorkload_Execute"); - BOOST_ASSERT(m_pDepthwiseConvolutionLayer); + ARMNN_ASSERT(m_pDepthwiseConvolutionLayer); m_pDepthwiseConvolutionLayer->run(); } diff --git a/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp index c62f71948c..ffca2076fe 100644 --- a/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp +++ b/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp @@ -38,7 +38,7 @@ arm_compute::Status NeonTransposeConvolution2dWorkloadValidate(const TensorInfo& if (descriptor.m_BiasEnabled) { - BOOST_ASSERT(biases.has_value()); + ARMNN_ASSERT(biases.has_value()); aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout); optionalAclBiasesInfo = &aclBiasesInfo; @@ -81,7 +81,7 @@ NeonTransposeConvolution2dWorkload::NeonTransposeConvolution2dWorkload( m_Layer = std::make_unique<arm_compute::NEDeconvolutionLayer>(memoryManager); m_Layer->configure(&input, m_KernelTensor.get(), m_BiasTensor.get(), &output, padStrideInfo); - BOOST_ASSERT(m_Layer); + ARMNN_ASSERT(m_Layer); InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight); diff --git a/src/backends/neon/workloads/NeonWorkloadUtils.hpp b/src/backends/neon/workloads/NeonWorkloadUtils.hpp index 3f0fe842aa..c3c9d3dbbc 100644 --- a/src/backends/neon/workloads/NeonWorkloadUtils.hpp +++ b/src/backends/neon/workloads/NeonWorkloadUtils.hpp @@ -35,7 +35,7 @@ void CopyArmComputeTensorData(arm_compute::Tensor& dstTensor, const T* srcData) inline void InitializeArmComputeTensorData(arm_compute::Tensor& tensor, const ConstCpuTensorHandle* handle) { - BOOST_ASSERT(handle); + ARMNN_ASSERT(handle); switch(handle->GetTensorInfo().GetDataType()) { @@ -59,7 +59,7 @@ inline void InitializeArmComputeTensorData(arm_compute::Tensor& tensor, CopyArmComputeTensorData(tensor, handle->GetConstTensor<int32_t>()); break; default: - BOOST_ASSERT_MSG(false, "Unexpected tensor type."); + ARMNN_ASSERT_MSG(false, "Unexpected tensor type."); } }; diff --git a/src/backends/reference/RefLayerSupport.cpp b/src/backends/reference/RefLayerSupport.cpp index 607c86b112..25d639a38a 100644 --- a/src/backends/reference/RefLayerSupport.cpp +++ b/src/backends/reference/RefLayerSupport.cpp @@ -348,7 +348,7 @@ bool RefLayerSupport::IsConcatSupported(const std::vector<const TensorInfo*> inp "Reference concatenation: output type not supported"); for (const TensorInfo* input : inputs) { - BOOST_ASSERT(input != nullptr); + ARMNN_ASSERT(input != nullptr); supported &= CheckSupportRule(TypeAnyOf(*input, supportedTypes), reasonIfUnsupported, "Reference concatenation: input type not supported"); @@ -1864,7 +1864,7 @@ bool RefLayerSupport::IsStackSupported(const std::vector<const TensorInfo*>& inp "Reference stack: output type not supported"); for (const TensorInfo* input : inputs) { - BOOST_ASSERT(input != nullptr); + ARMNN_ASSERT(input != nullptr); supported &= CheckSupportRule(TypeAnyOf(*input, supportedTypes), reasonIfUnsupported, "Reference stack: input type not supported"); diff --git a/src/backends/reference/RefMemoryManager.cpp b/src/backends/reference/RefMemoryManager.cpp index 4f15e39ee1..76054e41e1 100644 --- a/src/backends/reference/RefMemoryManager.cpp +++ b/src/backends/reference/RefMemoryManager.cpp @@ -4,7 +4,7 @@ // #include "RefMemoryManager.hpp" -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> #include <algorithm> @@ -35,7 +35,7 @@ RefMemoryManager::Pool* RefMemoryManager::Manage(unsigned int numBytes) void RefMemoryManager::Allocate(RefMemoryManager::Pool* pool) { - BOOST_ASSERT(pool); + ARMNN_ASSERT(pool); m_FreePools.push_back(pool); } @@ -75,25 +75,25 @@ RefMemoryManager::Pool::~Pool() void* RefMemoryManager::Pool::GetPointer() { - BOOST_ASSERT_MSG(m_Pointer, "RefMemoryManager::Pool::GetPointer() called when memory not acquired"); + ARMNN_ASSERT_MSG(m_Pointer, "RefMemoryManager::Pool::GetPointer() called when memory not acquired"); return m_Pointer; } void RefMemoryManager::Pool::Reserve(unsigned int numBytes) { - BOOST_ASSERT_MSG(!m_Pointer, "RefMemoryManager::Pool::Reserve() cannot be called after memory acquired"); + ARMNN_ASSERT_MSG(!m_Pointer, "RefMemoryManager::Pool::Reserve() cannot be called after memory acquired"); m_Size = std::max(m_Size, numBytes); } void RefMemoryManager::Pool::Acquire() { - BOOST_ASSERT_MSG(!m_Pointer, "RefMemoryManager::Pool::Acquire() called when memory already acquired"); + ARMNN_ASSERT_MSG(!m_Pointer, "RefMemoryManager::Pool::Acquire() called when memory already acquired"); m_Pointer = ::operator new(size_t(m_Size)); } void RefMemoryManager::Pool::Release() { - BOOST_ASSERT_MSG(m_Pointer, "RefMemoryManager::Pool::Release() called when memory not acquired"); + ARMNN_ASSERT_MSG(m_Pointer, "RefMemoryManager::Pool::Release() called when memory not acquired"); ::operator delete(m_Pointer); m_Pointer = nullptr; } diff --git a/src/backends/reference/RefTensorHandle.cpp b/src/backends/reference/RefTensorHandle.cpp index 84a74edc1d..7d86b110a7 100644 --- a/src/backends/reference/RefTensorHandle.cpp +++ b/src/backends/reference/RefTensorHandle.cpp @@ -44,8 +44,8 @@ RefTensorHandle::~RefTensorHandle() void RefTensorHandle::Manage() { - BOOST_ASSERT_MSG(!m_Pool, "RefTensorHandle::Manage() called twice"); - BOOST_ASSERT_MSG(!m_UnmanagedMemory, "RefTensorHandle::Manage() called after Allocate()"); + ARMNN_ASSERT_MSG(!m_Pool, "RefTensorHandle::Manage() called twice"); + ARMNN_ASSERT_MSG(!m_UnmanagedMemory, "RefTensorHandle::Manage() called after Allocate()"); m_Pool = m_MemoryManager->Manage(m_TensorInfo.GetNumBytes()); } @@ -84,7 +84,7 @@ void* RefTensorHandle::GetPointer() const } else { - BOOST_ASSERT_MSG(m_Pool, "RefTensorHandle::GetPointer called on unmanaged, unallocated tensor handle"); + ARMNN_ASSERT_MSG(m_Pool, "RefTensorHandle::GetPointer called on unmanaged, unallocated tensor handle"); return m_MemoryManager->GetPointer(m_Pool); } } @@ -92,14 +92,14 @@ void* RefTensorHandle::GetPointer() const void RefTensorHandle::CopyOutTo(void* dest) const { const void *src = GetPointer(); - BOOST_ASSERT(src); + ARMNN_ASSERT(src); memcpy(dest, src, m_TensorInfo.GetNumBytes()); } void RefTensorHandle::CopyInFrom(const void* src) { void *dest = GetPointer(); - BOOST_ASSERT(dest); + ARMNN_ASSERT(dest); memcpy(dest, src, m_TensorInfo.GetNumBytes()); } diff --git a/src/backends/reference/workloads/BaseIterator.hpp b/src/backends/reference/workloads/BaseIterator.hpp index f43e8b67a9..be20644ab7 100644 --- a/src/backends/reference/workloads/BaseIterator.hpp +++ b/src/backends/reference/workloads/BaseIterator.hpp @@ -5,14 +5,13 @@ #pragma once -#include <armnn/utility/IgnoreUnused.hpp> #include <armnn/TypesUtils.hpp> +#include <armnn/utility/Assert.hpp> +#include <armnn/utility/IgnoreUnused.hpp> #include <armnnUtils/FloatingPointConverter.hpp> #include <ResolveType.hpp> -#include <boost/assert.hpp> - namespace armnn { @@ -78,28 +77,28 @@ public: TypedIterator& operator++() override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); ++m_Iterator; return *this; } TypedIterator& operator+=(const unsigned int increment) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator += increment; return *this; } TypedIterator& operator-=(const unsigned int increment) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator -= increment; return *this; } TypedIterator& operator[](const unsigned int index) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator = m_Start + index; return *this; } @@ -107,7 +106,7 @@ public: TypedIterator& SetIndex(unsigned int index, unsigned int axisIndex = 0) override { IgnoreUnused(axisIndex); - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator = m_Start + index; return *this; } @@ -504,7 +503,7 @@ public: // This should be called to set index for per-axis Encoder/Decoder PerAxisIterator& SetIndex(unsigned int index, unsigned int axisIndex) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator = m_Start + index; m_AxisIndex = axisIndex; return *this; @@ -519,7 +518,7 @@ public: PerAxisIterator& operator++() override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); ++m_Iterator; m_AxisIndex = static_cast<unsigned int>(*m_Iterator) % m_AxisFactor; return *this; @@ -527,7 +526,7 @@ public: PerAxisIterator& operator+=(const unsigned int increment) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator += increment; m_AxisIndex = static_cast<unsigned int>(*m_Iterator) % m_AxisFactor; return *this; @@ -535,7 +534,7 @@ public: PerAxisIterator& operator-=(const unsigned int decrement) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator -= decrement; m_AxisIndex = static_cast<unsigned int>(*m_Iterator) % m_AxisFactor; return *this; @@ -543,7 +542,7 @@ public: PerAxisIterator& operator[](const unsigned int index) override { - BOOST_ASSERT(m_Iterator); + ARMNN_ASSERT(m_Iterator); m_Iterator = m_Start + index; m_AxisIndex = static_cast<unsigned int>(*m_Iterator) % m_AxisFactor; return *this; diff --git a/src/backends/reference/workloads/BatchToSpaceNd.cpp b/src/backends/reference/workloads/BatchToSpaceNd.cpp index 7efdb9b75c..bf7de1b04c 100644 --- a/src/backends/reference/workloads/BatchToSpaceNd.cpp +++ b/src/backends/reference/workloads/BatchToSpaceNd.cpp @@ -9,7 +9,7 @@ #include <armnn/Types.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> using namespace armnnUtils; @@ -42,11 +42,11 @@ void BatchToSpaceNd(const DataLayoutIndexed& dataLayout, { TensorShape inputShape = inputTensorInfo.GetShape(); - BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Expected Input with 4 Dimensions"); + ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Expected Input with 4 Dimensions"); TensorShape outputShape = outputTensorInfo.GetShape(); - BOOST_ASSERT_MSG(outputShape.GetNumDimensions() == 4, "Expected Output with 4 Dimensions"); + ARMNN_ASSERT_MSG(outputShape.GetNumDimensions() == 4, "Expected Output with 4 Dimensions"); const unsigned int inputBatchSize = inputShape[0]; const unsigned int channels = inputShape[dataLayout.GetChannelsIndex()]; @@ -55,12 +55,12 @@ void BatchToSpaceNd(const DataLayoutIndexed& dataLayout, const unsigned int outputHeight = outputShape[dataLayout.GetHeightIndex()]; const unsigned int outputWidth = outputShape[dataLayout.GetWidthIndex()]; - BOOST_ASSERT_MSG(blockShape.size() > 0, "BlockShape must contain 1 or more entries"); + ARMNN_ASSERT_MSG(blockShape.size() > 0, "BlockShape must contain 1 or more entries"); const unsigned int blockShapeHeight = blockShape[0]; const unsigned int blockShapeWidth = blockShape[1]; - BOOST_ASSERT_MSG(cropsData.size() > 0, "Crops must contain 1 or more entries"); + ARMNN_ASSERT_MSG(cropsData.size() > 0, "Crops must contain 1 or more entries"); const unsigned int cropsTop = cropsData[0].first; const unsigned int cropsLeft = cropsData[1].first; diff --git a/src/backends/reference/workloads/Concatenate.cpp b/src/backends/reference/workloads/Concatenate.cpp index bb55424c0c..a85e34ee61 100644 --- a/src/backends/reference/workloads/Concatenate.cpp +++ b/src/backends/reference/workloads/Concatenate.cpp @@ -38,7 +38,7 @@ void Concatenate(const ConcatQueueDescriptor &data) //Split view extents are defined by the size of (the corresponding) input tensor. const TensorInfo& inputInfo = GetTensorInfo(data.m_Inputs[viewIdx]); - BOOST_ASSERT(inputInfo.GetNumDimensions() == outputInfo0.GetNumDimensions()); + ARMNN_ASSERT(inputInfo.GetNumDimensions() == outputInfo0.GetNumDimensions()); // Check all dimensions to see if this element is inside the given input view. bool insideView = true; diff --git a/src/backends/reference/workloads/ConvImpl.cpp b/src/backends/reference/workloads/ConvImpl.cpp index 0c13e3ba0d..9d2f410a25 100644 --- a/src/backends/reference/workloads/ConvImpl.cpp +++ b/src/backends/reference/workloads/ConvImpl.cpp @@ -5,7 +5,7 @@ #include "ConvImpl.hpp" -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> #include <cmath> #include <limits> @@ -15,7 +15,7 @@ namespace armnn QuantizedMultiplierSmallerThanOne::QuantizedMultiplierSmallerThanOne(float multiplier) { - BOOST_ASSERT(multiplier >= 0.0f && multiplier < 1.0f); + ARMNN_ASSERT(multiplier >= 0.0f && multiplier < 1.0f); if (multiplier == 0.0f) { m_Multiplier = 0; @@ -26,14 +26,14 @@ QuantizedMultiplierSmallerThanOne::QuantizedMultiplierSmallerThanOne(float multi const double q = std::frexp(multiplier, &m_RightShift); m_RightShift = -m_RightShift; int64_t qFixed = static_cast<int64_t>(std::round(q * (1ll << 31))); - BOOST_ASSERT(qFixed <= (1ll << 31)); + ARMNN_ASSERT(qFixed <= (1ll << 31)); if (qFixed == (1ll << 31)) { qFixed /= 2; --m_RightShift; } - BOOST_ASSERT(m_RightShift >= 0); - BOOST_ASSERT(qFixed <= std::numeric_limits<int32_t>::max()); + ARMNN_ASSERT(m_RightShift >= 0); + ARMNN_ASSERT(qFixed <= std::numeric_limits<int32_t>::max()); m_Multiplier = static_cast<int32_t>(qFixed); } } @@ -61,7 +61,7 @@ int32_t QuantizedMultiplierSmallerThanOne::SaturatingRoundingDoublingHighMul(int int32_t QuantizedMultiplierSmallerThanOne::RoundingDivideByPOT(int32_t x, int exponent) { - BOOST_ASSERT(exponent >= 0 && exponent <= 31); + ARMNN_ASSERT(exponent >= 0 && exponent <= 31); int32_t mask = (1 << exponent) - 1; int32_t remainder = x & mask; int32_t threshold = (mask >> 1) + (x < 0 ? 1 : 0); diff --git a/src/backends/reference/workloads/ConvImpl.hpp b/src/backends/reference/workloads/ConvImpl.hpp index 562fd3e296..f5aa8f3447 100644 --- a/src/backends/reference/workloads/ConvImpl.hpp +++ b/src/backends/reference/workloads/ConvImpl.hpp @@ -15,7 +15,6 @@ #include <armnnUtils/DataLayoutIndexed.hpp> -#include <boost/assert.hpp> #include <boost/numeric/conversion/cast.hpp> #include <cmath> diff --git a/src/backends/reference/workloads/Decoders.hpp b/src/backends/reference/workloads/Decoders.hpp index 3434ccb764..deb3b1f4b2 100644 --- a/src/backends/reference/workloads/Decoders.hpp +++ b/src/backends/reference/workloads/Decoders.hpp @@ -10,7 +10,7 @@ #include <armnnUtils/FloatingPointConverter.hpp> #include <armnnUtils/TensorUtils.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> namespace armnn { @@ -142,7 +142,7 @@ inline std::unique_ptr<Decoder<float>> MakeDecoder(const TensorInfo& info, const } default: { - BOOST_ASSERT_MSG(false, "Unsupported Data Type!"); + ARMNN_ASSERT_MSG(false, "Unsupported Data Type!"); break; } } diff --git a/src/backends/reference/workloads/DepthToSpace.cpp b/src/backends/reference/workloads/DepthToSpace.cpp index 91ca160ae2..f5e9ec5498 100644 --- a/src/backends/reference/workloads/DepthToSpace.cpp +++ b/src/backends/reference/workloads/DepthToSpace.cpp @@ -8,7 +8,7 @@ #include <armnnUtils/DataLayoutIndexed.hpp> #include <armnnUtils/Permute.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> using namespace armnnUtils; @@ -22,7 +22,7 @@ void DepthToSpace(const TensorInfo& inputInfo, unsigned int dataTypeSize) { const unsigned int blockSize = descriptor.m_BlockSize; - BOOST_ASSERT(blockSize != 0u); + ARMNN_ASSERT(blockSize != 0u); const TensorShape& inputShape = inputInfo.GetShape(); const unsigned int batches = inputShape[0]; diff --git a/src/backends/reference/workloads/Dequantize.cpp b/src/backends/reference/workloads/Dequantize.cpp index 63c0405efe..fdc8e30c75 100644 --- a/src/backends/reference/workloads/Dequantize.cpp +++ b/src/backends/reference/workloads/Dequantize.cpp @@ -16,7 +16,7 @@ void Dequantize(Decoder<float>& inputDecoder, const TensorInfo& outputInfo) { IgnoreUnused(outputInfo); - BOOST_ASSERT(inputInfo.GetNumElements() == outputInfo.GetNumElements()); + ARMNN_ASSERT(inputInfo.GetNumElements() == outputInfo.GetNumElements()); for (unsigned int i = 0; i < inputInfo.GetNumElements(); i++) { // inputDecoder.Get() dequantizes the data element from whatever diff --git a/src/backends/reference/workloads/DetectionPostProcess.cpp b/src/backends/reference/workloads/DetectionPostProcess.cpp index 57cf01e4a1..61a504ec6b 100644 --- a/src/backends/reference/workloads/DetectionPostProcess.cpp +++ b/src/backends/reference/workloads/DetectionPostProcess.cpp @@ -5,8 +5,8 @@ #include "DetectionPostProcess.hpp" +#include <armnn/utility/Assert.hpp> -#include <boost/assert.hpp> #include <boost/numeric/conversion/cast.hpp> #include <algorithm> @@ -213,8 +213,8 @@ void DetectionPostProcess(const TensorInfo& boxEncodingsInfo, // xmax boxCorners[indexW] = xCentre + halfW; - BOOST_ASSERT(boxCorners[indexY] < boxCorners[indexH]); - BOOST_ASSERT(boxCorners[indexX] < boxCorners[indexW]); + ARMNN_ASSERT(boxCorners[indexY] < boxCorners[indexH]); + ARMNN_ASSERT(boxCorners[indexX] < boxCorners[indexW]); } unsigned int numClassesWithBg = desc.m_NumClasses + 1; diff --git a/src/backends/reference/workloads/Encoders.hpp b/src/backends/reference/workloads/Encoders.hpp index e93987da31..c0524a7719 100644 --- a/src/backends/reference/workloads/Encoders.hpp +++ b/src/backends/reference/workloads/Encoders.hpp @@ -9,7 +9,7 @@ #include <armnnUtils/TensorUtils.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> namespace armnn { @@ -89,7 +89,7 @@ inline std::unique_ptr<Encoder<float>> MakeEncoder(const TensorInfo& info, void* } default: { - BOOST_ASSERT_MSG(false, "Unsupported target Data Type!"); + ARMNN_ASSERT_MSG(false, "Unsupported target Data Type!"); break; } } @@ -107,7 +107,7 @@ inline std::unique_ptr<Encoder<bool>> MakeEncoder(const TensorInfo& info, void* } default: { - BOOST_ASSERT_MSG(false, "Cannot encode from boolean. Not supported target Data Type!"); + ARMNN_ASSERT_MSG(false, "Cannot encode from boolean. Not supported target Data Type!"); break; } } diff --git a/src/backends/reference/workloads/FullyConnected.cpp b/src/backends/reference/workloads/FullyConnected.cpp index 02d9b060ef..5a87520f84 100644 --- a/src/backends/reference/workloads/FullyConnected.cpp +++ b/src/backends/reference/workloads/FullyConnected.cpp @@ -7,8 +7,6 @@ #include "RefWorkloadUtils.hpp" -#include <boost/assert.hpp> - namespace armnn { diff --git a/src/backends/reference/workloads/Gather.cpp b/src/backends/reference/workloads/Gather.cpp index 4cf3a142a0..c23edcd3bd 100644 --- a/src/backends/reference/workloads/Gather.cpp +++ b/src/backends/reference/workloads/Gather.cpp @@ -36,7 +36,7 @@ void Gather(const TensorInfo& paramsInfo, { unsigned int indx = boost::numeric_cast<unsigned int>(indices[i]); - BOOST_ASSERT(indices[i] >= 0 && indx < paramsShape[0]); + ARMNN_ASSERT(indices[i] >= 0 && indx < paramsShape[0]); unsigned int startOffset = indx * paramsProduct; unsigned int endOffset = startOffset + paramsProduct; @@ -51,7 +51,7 @@ void Gather(const TensorInfo& paramsInfo, } } - BOOST_ASSERT(outIndex == outputInfo.GetNumElements()); + ARMNN_ASSERT(outIndex == outputInfo.GetNumElements()); } } //namespace armnn diff --git a/src/backends/reference/workloads/LogSoftmax.cpp b/src/backends/reference/workloads/LogSoftmax.cpp index 103d62a8df..1998f50c87 100644 --- a/src/backends/reference/workloads/LogSoftmax.cpp +++ b/src/backends/reference/workloads/LogSoftmax.cpp @@ -6,11 +6,11 @@ #include "LogSoftmax.hpp" #include <armnnUtils/TensorUtils.hpp> +#include <armnn/utility/Assert.hpp> #include <armnn/utility/IgnoreUnused.hpp> #include <cmath> -#include <boost/assert.hpp> #include <boost/numeric/conversion/cast.hpp> namespace @@ -35,7 +35,7 @@ void LogSoftmax(Decoder<float>& input, const unsigned int numDimensions = inputInfo.GetNumDimensions(); bool axisIsValid = ValidateAxis(descriptor.m_Axis, numDimensions); - BOOST_ASSERT_MSG(axisIsValid, + ARMNN_ASSERT_MSG(axisIsValid, "Axis index is not in range [-numDimensions, numDimensions)."); IgnoreUnused(axisIsValid); diff --git a/src/backends/reference/workloads/Mean.cpp b/src/backends/reference/workloads/Mean.cpp index f2c0a4fc3f..72080ef042 100644 --- a/src/backends/reference/workloads/Mean.cpp +++ b/src/backends/reference/workloads/Mean.cpp @@ -128,7 +128,7 @@ void Mean(const armnn::TensorInfo& inputInfo, for (unsigned int idx = 0; idx < numResolvedAxis; ++idx) { unsigned int current = inputDims[resolvedAxis[idx]]; - BOOST_ASSERT(boost::numeric_cast<float>(current) < + ARMNN_ASSERT(boost::numeric_cast<float>(current) < (std::numeric_limits<float>::max() / boost::numeric_cast<float>(numElementsInAxis))); numElementsInAxis *= current; } diff --git a/src/backends/reference/workloads/RefConstantWorkload.cpp b/src/backends/reference/workloads/RefConstantWorkload.cpp index 3506198410..d3e65e6615 100644 --- a/src/backends/reference/workloads/RefConstantWorkload.cpp +++ b/src/backends/reference/workloads/RefConstantWorkload.cpp @@ -9,7 +9,7 @@ #include <armnn/Types.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> #include <cstring> @@ -24,10 +24,10 @@ void RefConstantWorkload::PostAllocationConfigure() { const ConstantQueueDescriptor& data = this->m_Data; - BOOST_ASSERT(data.m_LayerOutput != nullptr); + ARMNN_ASSERT(data.m_LayerOutput != nullptr); const TensorInfo& outputInfo = GetTensorInfo(data.m_Outputs[0]); - BOOST_ASSERT(data.m_LayerOutput->GetTensorInfo().GetNumBytes() == outputInfo.GetNumBytes()); + ARMNN_ASSERT(data.m_LayerOutput->GetTensorInfo().GetNumBytes() == outputInfo.GetNumBytes()); memcpy(GetOutputTensorData<void>(0, data), data.m_LayerOutput->GetConstTensor<void>(), outputInfo.GetNumBytes()); diff --git a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp index ac82db90e5..f8c3548905 100644 --- a/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp +++ b/src/backends/reference/workloads/RefFullyConnectedWorkload.cpp @@ -32,7 +32,7 @@ RefFullyConnectedWorkload::RefFullyConnectedWorkload( void RefFullyConnectedWorkload::PostAllocationConfigure() { const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]); - BOOST_ASSERT(inputInfo.GetNumDimensions() > 1); + ARMNN_ASSERT(inputInfo.GetNumDimensions() > 1); m_InputShape = inputInfo.GetShape(); m_InputDecoder = MakeDecoder<float>(inputInfo); diff --git a/src/backends/reference/workloads/RefLogSoftmaxWorkload.cpp b/src/backends/reference/workloads/RefLogSoftmaxWorkload.cpp index a987e79dda..a2ace13144 100644 --- a/src/backends/reference/workloads/RefLogSoftmaxWorkload.cpp +++ b/src/backends/reference/workloads/RefLogSoftmaxWorkload.cpp @@ -12,7 +12,7 @@ #include <Profiling.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> namespace armnn { @@ -27,8 +27,8 @@ void RefLogSoftmaxWorkload::Execute() const std::unique_ptr<Decoder<float>> decoder = MakeDecoder<float>(inputInfo, m_Data.m_Inputs[0]->Map()); std::unique_ptr<Encoder<float>> encoder = MakeEncoder<float>(outputInfo, m_Data.m_Outputs[0]->Map()); - BOOST_ASSERT(decoder != nullptr); - BOOST_ASSERT(encoder != nullptr); + ARMNN_ASSERT(decoder != nullptr); + ARMNN_ASSERT(encoder != nullptr); LogSoftmax(*decoder, *encoder, inputInfo, m_Data.m_Parameters); } diff --git a/src/backends/reference/workloads/RefStackWorkload.cpp b/src/backends/reference/workloads/RefStackWorkload.cpp index be36f40633..fc859506a3 100644 --- a/src/backends/reference/workloads/RefStackWorkload.cpp +++ b/src/backends/reference/workloads/RefStackWorkload.cpp @@ -26,7 +26,7 @@ void RefStackWorkload::Execute() const if (!m_Data.m_Parameters.m_Axis) { float* output = GetOutputTensorData<float>(0, m_Data); - BOOST_ASSERT(output != nullptr); + ARMNN_ASSERT(output != nullptr); unsigned int numInputs = m_Data.m_Parameters.m_NumInputs; unsigned int inputLength = GetTensorInfo(m_Data.m_Inputs[0]).GetNumElements(); diff --git a/src/backends/reference/workloads/RefStridedSliceWorkload.cpp b/src/backends/reference/workloads/RefStridedSliceWorkload.cpp index bfd3c284ae..e994a09230 100644 --- a/src/backends/reference/workloads/RefStridedSliceWorkload.cpp +++ b/src/backends/reference/workloads/RefStridedSliceWorkload.cpp @@ -27,7 +27,7 @@ void RefStridedSliceWorkload::Execute() const DataType inputDataType = inputInfo.GetDataType(); DataType outputDataType = outputInfo.GetDataType(); - BOOST_ASSERT(inputDataType == outputDataType); + ARMNN_ASSERT(inputDataType == outputDataType); IgnoreUnused(outputDataType); StridedSlice(inputInfo, diff --git a/src/backends/reference/workloads/Slice.cpp b/src/backends/reference/workloads/Slice.cpp index 0223cdc56a..e972524f11 100644 --- a/src/backends/reference/workloads/Slice.cpp +++ b/src/backends/reference/workloads/Slice.cpp @@ -5,9 +5,9 @@ #include "Slice.hpp" +#include <armnn/utility/Assert.hpp> #include <armnn/utility/IgnoreUnused.hpp> -#include <boost/assert.hpp> #include <boost/numeric/conversion/cast.hpp> namespace armnn @@ -22,11 +22,11 @@ void Slice(const TensorInfo& inputInfo, const TensorShape& inputShape = inputInfo.GetShape(); const unsigned int numDims = inputShape.GetNumDimensions(); - BOOST_ASSERT(descriptor.m_Begin.size() == numDims); - BOOST_ASSERT(descriptor.m_Size.size() == numDims); + ARMNN_ASSERT(descriptor.m_Begin.size() == numDims); + ARMNN_ASSERT(descriptor.m_Size.size() == numDims); constexpr unsigned int maxNumDims = 4; - BOOST_ASSERT(numDims <= maxNumDims); + ARMNN_ASSERT(numDims <= maxNumDims); std::vector<unsigned int> paddedInput(4); std::vector<unsigned int> paddedBegin(4); @@ -65,10 +65,10 @@ void Slice(const TensorInfo& inputInfo, unsigned int size2 = paddedSize[2]; unsigned int size3 = paddedSize[3]; - BOOST_ASSERT(begin0 + size0 <= dim0); - BOOST_ASSERT(begin1 + size1 <= dim1); - BOOST_ASSERT(begin2 + size2 <= dim2); - BOOST_ASSERT(begin3 + size3 <= dim3); + ARMNN_ASSERT(begin0 + size0 <= dim0); + ARMNN_ASSERT(begin1 + size1 <= dim1); + ARMNN_ASSERT(begin2 + size2 <= dim2); + ARMNN_ASSERT(begin3 + size3 <= dim3); const unsigned char* input = reinterpret_cast<const unsigned char*>(inputData); unsigned char* output = reinterpret_cast<unsigned char*>(outputData); diff --git a/src/backends/reference/workloads/Softmax.cpp b/src/backends/reference/workloads/Softmax.cpp index 5036389a10..32eca84849 100644 --- a/src/backends/reference/workloads/Softmax.cpp +++ b/src/backends/reference/workloads/Softmax.cpp @@ -16,9 +16,9 @@ namespace armnn /// Computes the softmax function on some inputs, into outputs, with a shape given by tensorInfo. void Softmax(Decoder<float>& in, Encoder<float>& out, const TensorInfo& inputTensorInfo, float beta, int axis) { - BOOST_ASSERT_MSG(axis < static_cast<int>(inputTensorInfo.GetNumDimensions()), + ARMNN_ASSERT_MSG(axis < static_cast<int>(inputTensorInfo.GetNumDimensions()), "Required axis index greater than number of dimensions."); - BOOST_ASSERT_MSG(axis >= -static_cast<int>(inputTensorInfo.GetNumDimensions()), + ARMNN_ASSERT_MSG(axis >= -static_cast<int>(inputTensorInfo.GetNumDimensions()), "Required axis index lower than negative of the number of dimensions"); unsigned int uAxis = axis < 0 ? diff --git a/src/backends/reference/workloads/Splitter.cpp b/src/backends/reference/workloads/Splitter.cpp index 3bddfb0cab..09edc5e0f5 100644 --- a/src/backends/reference/workloads/Splitter.cpp +++ b/src/backends/reference/workloads/Splitter.cpp @@ -6,8 +6,7 @@ #include "RefWorkloadUtils.hpp" #include <backendsCommon/WorkloadData.hpp> #include <armnn/Tensor.hpp> - -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> #include "Splitter.hpp" #include <cmath> @@ -47,7 +46,7 @@ void Split(const SplitterQueueDescriptor& data) //Split view extents are defined by the size of (the corresponding) input tensor. const TensorInfo& outputInfo = GetTensorInfo(data.m_Outputs[viewIdx]); - BOOST_ASSERT(outputInfo.GetNumDimensions() == inputInfo.GetNumDimensions()); + ARMNN_ASSERT(outputInfo.GetNumDimensions() == inputInfo.GetNumDimensions()); // Check all dimensions to see if this element is inside the given input view. bool insideView = true; diff --git a/src/backends/reference/workloads/Splitter.hpp b/src/backends/reference/workloads/Splitter.hpp index 271c6fdeb8..26309b080f 100644 --- a/src/backends/reference/workloads/Splitter.hpp +++ b/src/backends/reference/workloads/Splitter.hpp @@ -8,7 +8,7 @@ #include "RefWorkloadUtils.hpp" #include <backendsCommon/WorkloadData.hpp> #include <armnn/Tensor.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> namespace armnn { @@ -38,7 +38,7 @@ void Splitter(const SplitterQueueDescriptor& data) //Split view extents are defined by the size of (the corresponding) input tensor. const TensorInfo& outputInfo = GetTensorInfo(data.m_Outputs[viewIdx]); - BOOST_ASSERT(outputInfo.GetNumDimensions() == inputInfo0.GetNumDimensions()); + ARMNN_ASSERT(outputInfo.GetNumDimensions() == inputInfo0.GetNumDimensions()); // Check all dimensions to see if this element is inside the given input view. bool insideView = true; @@ -67,10 +67,10 @@ void Splitter(const SplitterQueueDescriptor& data) //We are within the view, to copy input data to the output corresponding to this view. DataType* outputData = GetOutputTensorData<DataType>(viewIdx, data); - BOOST_ASSERT(outputData); + ARMNN_ASSERT(outputData); const DataType* inputData = GetInputTensorData<DataType>(0, data); - BOOST_ASSERT(inputData); + ARMNN_ASSERT(inputData); outputData[outIndex] = inputData[index]; } diff --git a/src/backends/reference/workloads/StridedSlice.cpp b/src/backends/reference/workloads/StridedSlice.cpp index 62f06dc5ec..b00b049ff6 100644 --- a/src/backends/reference/workloads/StridedSlice.cpp +++ b/src/backends/reference/workloads/StridedSlice.cpp @@ -7,7 +7,8 @@ #include <ResolveType.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> + #include <boost/numeric/conversion/cast.hpp> #include <cstring> @@ -20,12 +21,12 @@ namespace void PadParams(StridedSliceDescriptor& p, unsigned int dimCount) { - BOOST_ASSERT_MSG(dimCount <= 4, "Expected input with at most 4 dimensions"); + ARMNN_ASSERT_MSG(dimCount <= 4, "Expected input with at most 4 dimensions"); const unsigned int beginIndicesCount = boost::numeric_cast<unsigned int>(p.m_Begin.size()); - BOOST_ASSERT(dimCount >= beginIndicesCount); + ARMNN_ASSERT(dimCount >= beginIndicesCount); const unsigned int padCount = dimCount - beginIndicesCount; p.m_Begin.resize(dimCount); diff --git a/src/backends/reference/workloads/TensorBufferArrayView.hpp b/src/backends/reference/workloads/TensorBufferArrayView.hpp index e03c42fe60..5d66fd5273 100644 --- a/src/backends/reference/workloads/TensorBufferArrayView.hpp +++ b/src/backends/reference/workloads/TensorBufferArrayView.hpp @@ -9,7 +9,7 @@ #include <armnnUtils/DataLayoutIndexed.hpp> -#include <boost/assert.hpp> +#include <armnn/utility/Assert.hpp> namespace armnn { @@ -25,7 +25,7 @@ public: , m_Data(data) , m_DataLayout(dataLayout) { - BOOST_ASSERT(m_Shape.GetNumDimensions() == 4); + ARMNN_ASSERT(m_Shape.GetNumDimensions() == 4); } DataType& Get(unsigned int b, unsigned int c, unsigned int h, unsigned int w) const |