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
diff --git a/src/backends/backendsCommon/CpuTensorHandle.cpp b/src/backends/backendsCommon/CpuTensorHandle.cpp
index 65e6c47..7bcf59f 100644
--- a/src/backends/backendsCommon/CpuTensorHandle.cpp
+++ b/src/backends/backendsCommon/CpuTensorHandle.cpp
@@ -118,8 +118,8 @@
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 e6e59fc..78efb08 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 @@
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 @@
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 @@
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 03bec53..ddecc82 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 @@
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 8abc8a6..5601822 100644
--- a/src/backends/backendsCommon/MakeWorkloadHelper.hpp
+++ b/src/backends/backendsCommon/MakeWorkloadHelper.hpp
@@ -70,7 +70,7 @@
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 984443b..244b5f1 100644
--- a/src/backends/backendsCommon/Workload.hpp
+++ b/src/backends/backendsCommon/Workload.hpp
@@ -65,9 +65,9 @@
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 @@
{
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 @@
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 @@
{
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 f968ad7..1f4a849 100644
--- a/src/backends/backendsCommon/WorkloadData.cpp
+++ b/src/backends/backendsCommon/WorkloadData.cpp
@@ -40,7 +40,7 @@
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 5628c36..a7e8576 100644
--- a/src/backends/backendsCommon/WorkloadFactory.cpp
+++ b/src/backends/backendsCommon/WorkloadFactory.cpp
@@ -194,7 +194,7 @@
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 @@
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 @@
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 @@
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 @@
}
default:
{
- BOOST_ASSERT_MSG(false, "Unexpected bias type");
+ ARMNN_ASSERT_MSG(false, "Unexpected bias type");
}
}
}
@@ -1156,12 +1156,12 @@
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 @@
}
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 3b3959b..bd5e81e 100644
--- a/src/backends/backendsCommon/WorkloadUtils.cpp
+++ b/src/backends/backendsCommon/WorkloadUtils.cpp
@@ -13,8 +13,8 @@
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 @@
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 66056db..a4da924 100644
--- a/src/backends/backendsCommon/WorkloadUtils.hpp
+++ b/src/backends/backendsCommon/WorkloadUtils.hpp
@@ -168,8 +168,8 @@
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 116bf77..abdaa81 100644
--- a/src/backends/backendsCommon/test/MockBackend.cpp
+++ b/src/backends/backendsCommon/test/MockBackend.cpp
@@ -23,7 +23,7 @@
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 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 @@
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 @@
unsupportedSubgraphs.end(),
[&optimizationViews](const SubgraphView::SubgraphViewPtr& unsupportedSubgraph)
{
- BOOST_ASSERT(unsupportedSubgraph != nullptr);
+ ARMNN_ASSERT(unsupportedSubgraph != nullptr);
optimizationViews.AddFailedSubgraph(SubgraphView(*unsupportedSubgraph));
});
@@ -256,7 +256,7 @@
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 df001b7..9f38e47 100644
--- a/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
+++ b/src/backends/backendsCommon/test/WorkloadTestUtils.hpp
@@ -106,7 +106,7 @@
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 319434e..a82048c 100644
--- a/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ActivationTestImpl.cpp
@@ -1212,9 +1212,9 @@
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 2156b0e..a6b703b 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 @@
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 1e40b42..9e08e30 100644
--- a/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/ConcatTestImpl.cpp
@@ -61,7 +61,7 @@
}
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 @@
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 @@
}
else
{
- BOOST_ASSERT(expandedConcatAxis == 0);
+ ARMNN_ASSERT(expandedConcatAxis == 0);
concatDim = 0;
}
}
@@ -127,7 +127,7 @@
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 @@
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 @@
// 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 @@
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 @@
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 50ad667..c66027e 100644
--- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp
@@ -169,9 +169,9 @@
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 @@
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 @@
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 @@
// 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 @@
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 c277d2d..c64fc88 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 772ae2c..953b543 100644
--- a/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/SoftmaxTestImpl.cpp
@@ -104,7 +104,7 @@
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), input.origin());
- BOOST_ASSERT(workload);
+ ARMNN_ASSERT(workload);
ExecuteWorkload(*workload, memoryManager);