From 4d07e5e0e2f32184e395f44cc50eedf3de284d22 Mon Sep 17 00:00:00 2001 From: Narumol Prangnawarat Date: Mon, 6 Apr 2020 16:46:21 +0100 Subject: IVGCVSW-4485 Remove Boost assert Signed-off-by: Narumol Prangnawarat Change-Id: If602024a339df7548333e470545f9400c3daf7b3 --- ConversionUtils.cpp | 4 ++-- ConversionUtils.hpp | 24 ++++++++++++------------ RequestThread.cpp | 4 ++-- Utils.cpp | 7 ++++--- test/1.2/Capabilities.cpp | 10 ++++++---- test/TestTensor.cpp | 2 +- test/TestTensor.hpp | 4 +++- 7 files changed, 30 insertions(+), 25 deletions(-) diff --git a/ConversionUtils.cpp b/ConversionUtils.cpp index 09e51598..4c773964 100644 --- a/ConversionUtils.cpp +++ b/ConversionUtils.cpp @@ -31,7 +31,7 @@ bool LayerInputHandle::IsValid() const void LayerInputHandle::Connect(armnn::IInputSlot& inputSlot) { - BOOST_ASSERT(IsValid()); + ARMNN_ASSERT(IsValid()); if (m_OutputSlot) { m_OutputSlot->Connect(inputSlot); @@ -103,7 +103,7 @@ armnn::IConnectableLayer* ProcessActivation(const armnn::TensorInfo& tensorInfo, armnn::IConnectableLayer* prevLayer, ConversionData& data) { - BOOST_ASSERT(prevLayer->GetNumOutputSlots() == 1); + ARMNN_ASSERT(prevLayer->GetNumOutputSlots() == 1); prevLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo); diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp index 8067e53b..3b01b40f 100644 --- a/ConversionUtils.hpp +++ b/ConversionUtils.hpp @@ -10,6 +10,7 @@ #include #include #include +#include #include #include @@ -21,7 +22,6 @@ #include #include -#include #include #include @@ -269,7 +269,7 @@ armnn::IConnectableLayer& AddReshapeLayer(armnn::INetwork& network, reshapeDescriptor.m_TargetShape = reshapeInfo.GetShape(); armnn::IConnectableLayer* reshapeLayer = network.AddReshapeLayer(reshapeDescriptor); - BOOST_ASSERT(reshapeLayer != nullptr); + ARMNN_ASSERT(reshapeLayer != nullptr); // Attach the input layer to the reshape layer inputLayer.Connect(reshapeLayer->GetInputSlot(0)); @@ -283,7 +283,7 @@ bool BroadcastTensor(LayerInputHandle& input0, armnn::IConnectableLayer* startLayer, ConversionData& data) { - BOOST_ASSERT(startLayer != nullptr); + ARMNN_ASSERT(startLayer != nullptr); const armnn::TensorInfo& inputInfo0 = input0.GetTensorInfo(); const armnn::TensorInfo& inputInfo1 = input1.GetTensorInfo(); @@ -338,7 +338,7 @@ bool BroadcastTensor(LayerInputHandle& input0, return false; } - BOOST_ASSERT(data.m_Network != nullptr); + ARMNN_ASSERT(data.m_Network != nullptr); armnn::IConnectableLayer& reshapeLayer = AddReshapeLayer(*data.m_Network, smallInputHandle, reshapedInfo); if (input0IsSmaller) @@ -498,7 +498,7 @@ armnn::IConnectableLayer& AddTransposeLayer(armnn::INetwork& network, OSlot& inp // Add swizzle layer armnn::IConnectableLayer* const layer = network.AddTransposeLayer(mappings); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); // Connect input to swizzle layer input.Connect(layer->GetInputSlot(0)); @@ -619,7 +619,7 @@ bool CreateConcatPermutationParameters(const unsigned int numberOfDimensions, std::pair & permutationPair) { bool needPermute = false; - BOOST_ASSERT(numberOfDimensions >= 3); + ARMNN_ASSERT(numberOfDimensions >= 3); // ArmNN uses Compute Library subtensors to perform concatenation // This only works when concatenating along dimension 0, 1 or 3 for a 4-D tensor, @@ -685,7 +685,7 @@ const HalOperand* GetInputOperand(const HalOperation& operation, } // Model should have been validated beforehand - BOOST_ASSERT(operation.inputs[inputIndex] < getMainModel(model).operands.size()); + ARMNN_ASSERT(operation.inputs[inputIndex] < getMainModel(model).operands.size()); return &getMainModel(model).operands[operation.inputs[inputIndex]]; } @@ -704,7 +704,7 @@ const HalOperand* GetOutputOperand(const HalOperation& operation, } // Model should have been validated beforehand - BOOST_ASSERT(operation.outputs[outputIndex] < getMainModel(model).operands.size()); + ARMNN_ASSERT(operation.outputs[outputIndex] < getMainModel(model).operands.size()); return &getMainModel(model).operands[operation.outputs[outputIndex]]; } @@ -1453,7 +1453,7 @@ bool ConvertToActivation(const HalOperation& operation, } armnn::IConnectableLayer* layer = data.m_Network->AddActivationLayer(activationDesc); - BOOST_ASSERT(layer != nullptr); + ARMNN_ASSERT(layer != nullptr); input.Connect(layer->GetInputSlot(0)); return SetupAndTrackLayerOutputSlot(operation, 0, *layer, model, data); @@ -1950,7 +1950,7 @@ bool ConvertConcatenation(const HalOperation& operation, const HalModel& model, } } - BOOST_ASSERT(inputShapes.size() == inputHandles.size()); + ARMNN_ASSERT(inputShapes.size() == inputHandles.size()); if (inputsHaveBeenReshaped) { @@ -2677,7 +2677,7 @@ DequantizeResult DequantizeIfRequired(size_t operand_index, } const HalOperand* operand = GetInputOperand(operationIt, 0, model); - BOOST_ASSERT(operand); + ARMNN_ASSERT(operand); if (!IsQSymm8(*operand)) { @@ -2701,7 +2701,7 @@ DequantizeResult DequantizeIfRequired(size_t operand_index, for (size_t i = 0; i < dequantizedBufferLength; ++i) { float* dstPtr = dequantizedBuffer.get(); - BOOST_ASSERT(dstPtr); + ARMNN_ASSERT(dstPtr); *dstPtr++ = quantizedBuffer[i] * quantizationScale; } diff --git a/RequestThread.cpp b/RequestThread.cpp index 50c5161c..a177b1a4 100644 --- a/RequestThread.cpp +++ b/RequestThread.cpp @@ -17,7 +17,7 @@ #include "ArmnnPreparedModel_1_3.hpp" #endif -#include +#include #include @@ -135,7 +135,7 @@ void RequestThread::Process() default: // this should be unreachable ALOGE("RequestThread::Process() - invalid message type"); - BOOST_ASSERT_MSG(false, "ArmNN: RequestThread: invalid message type"); + ARMNN_ASSERT_MSG(false, "ArmNN: RequestThread: invalid message type"); } } } diff --git a/Utils.cpp b/Utils.cpp index 00d61c7b..a7df499c 100644 --- a/Utils.cpp +++ b/Utils.cpp @@ -11,6 +11,7 @@ #include #include +#include #include #include @@ -146,7 +147,7 @@ armnn::TensorInfo GetTensorInfoForOperand(const V1_2::Operand& operand) if (perChannel) { // ExtraParams is expected to be of type channelQuant - BOOST_ASSERT(operand.extraParams.getDiscriminator() == + ARMNN_ASSERT(operand.extraParams.getDiscriminator() == V1_2::Operand::ExtraParams::hidl_discriminator::channelQuant); auto perAxisQuantParams = operand.extraParams.channelQuant(); @@ -210,7 +211,7 @@ armnn::TensorInfo GetTensorInfoForOperand(const V1_3::Operand& operand) if (perChannel) { // ExtraParams is expected to be of type channelQuant - BOOST_ASSERT(operand.extraParams.getDiscriminator() == + ARMNN_ASSERT(operand.extraParams.getDiscriminator() == V1_2::Operand::ExtraParams::hidl_discriminator::channelQuant); auto perAxisQuantParams = operand.extraParams.channelQuant(); @@ -415,7 +416,7 @@ void DumpJsonProfilingIfRequired(bool gpuProfilingEnabled, return; } - BOOST_ASSERT(profiler); + ARMNN_ASSERT(profiler); // Set the name of the output profiling file. const std::string fileName = boost::str(boost::format("%1%/%2%_%3%.json") diff --git a/test/1.2/Capabilities.cpp b/test/1.2/Capabilities.cpp index 5f817591..f25723de 100644 --- a/test/1.2/Capabilities.cpp +++ b/test/1.2/Capabilities.cpp @@ -7,6 +7,8 @@ #include "Utils.h" +#include + #include #include @@ -60,8 +62,8 @@ void CheckOperandType(const V1_2::Capabilities& capabilities, V1_2::OperandType { using namespace armnn_driver::hal_1_2; PerformanceInfo perfInfo = android::nn::lookup(capabilities.operandPerformance, type); - BOOST_ASSERT(perfInfo.execTime == execTime); - BOOST_ASSERT(perfInfo.powerUsage == powerUsage); + ARMNN_ASSERT(perfInfo.execTime == execTime); + ARMNN_ASSERT(perfInfo.powerUsage == powerUsage); } BOOST_FIXTURE_TEST_SUITE(CapabilitiesTests, CapabilitiesFixture) @@ -92,7 +94,7 @@ BOOST_AUTO_TEST_CASE(PerformanceCapabilitiesWithRuntime) CheckOperandType(capabilities, V1_2::OperandType::OEM, FLT_MAX, FLT_MAX); CheckOperandType(capabilities, V1_2::OperandType::TENSOR_OEM_BYTE, FLT_MAX, FLT_MAX); - BOOST_ASSERT(error == V1_0::ErrorStatus::NONE); + ARMNN_ASSERT(error == V1_0::ErrorStatus::NONE); }; __system_property_set("Armnn.operandTypeTensorFloat32Performance.execTime", "2.0f"); @@ -153,7 +155,7 @@ BOOST_AUTO_TEST_CASE(PerformanceCapabilitiesUndefined) CheckOperandType(capabilities, V1_2::OperandType::OEM, FLT_MAX, FLT_MAX); CheckOperandType(capabilities, V1_2::OperandType::TENSOR_OEM_BYTE, FLT_MAX, FLT_MAX); - BOOST_ASSERT(error == V1_0::ErrorStatus::NONE); + ARMNN_ASSERT(error == V1_0::ErrorStatus::NONE); }; armnn::IRuntime::CreationOptions options; diff --git a/test/TestTensor.cpp b/test/TestTensor.cpp index a8045c5b..e6cb446f 100644 --- a/test/TestTensor.cpp +++ b/test/TestTensor.cpp @@ -25,7 +25,7 @@ unsigned int TestTensor::GetNumElements() const const float * TestTensor::GetData() const { - BOOST_ASSERT(m_Data.empty() == false); + ARMNN_ASSERT(m_Data.empty() == false); return &m_Data[0]; } diff --git a/test/TestTensor.hpp b/test/TestTensor.hpp index 623c9fbd..1cd1950d 100644 --- a/test/TestTensor.hpp +++ b/test/TestTensor.hpp @@ -6,6 +6,8 @@ #include "../ArmnnDriver.hpp" +#include + namespace driverTestHelpers { @@ -17,7 +19,7 @@ public: : m_Shape{shape} , m_Data{data} { - BOOST_ASSERT(m_Shape.GetNumElements() == m_Data.size()); + ARMNN_ASSERT(m_Shape.GetNumElements() == m_Data.size()); } hidl_vec GetDimensions() const; -- cgit v1.2.1