)
# The generated tensorflow protobuf .cc files are not warning clean and we can't fix them.
if(COMPILER_IS_GNU_LIKE)
- set_source_files_properties(${TF_PROTOBUFS} PROPERTIES COMPILE_FLAGS "-Wno-conversion -Wno-sign-conversion")
+ set_source_files_properties(${TF_PROTOBUFS} PROPERTIES COMPILE_FLAGS "-Wno-unused-variable -Wno-unused-parameter -Wno-conversion -Wno-sign-conversion")
endif()
add_library_ex(armnnTfParser SHARED ${armnn_tf_parser_sources})
# Compiler flags that are always set
set(CMAKE_POSITION_INDEPENDENT_CODE ON)
if(COMPILER_IS_GNU_LIKE)
- set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14 -Wall -Werror -Wold-style-cast -Wno-missing-braces -Wconversion -Wsign-conversion")
+ set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14 -Wall -Wextra -Werror -Wold-style-cast -Wno-missing-braces -Wconversion -Wsign-conversion")
elseif(${CMAKE_CXX_COMPILER_ID} STREQUAL MSVC)
# Disable C4996 (use of deprecated identifier) due to https://developercommunity.visualstudio.com/content/problem/252574/deprecated-compilation-warning-for-virtual-overrid.html
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /EHsc /MP /wd4996")
{
template<typename T>
-bool CompatibleTypes(DataType dataType)
+bool CompatibleTypes(DataType)
{
return false;
}
template<typename ... Params>
bool FalseFuncF16(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with float16 data type");
return false;
}
template<typename ... Params>
bool FalseFuncF32(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with float32 data type");
return false;
}
template<typename ... Params>
bool FalseFuncU8(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with 8-bit data type");
return false;
}
template<typename ... Params>
bool FalseFuncI32(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with int32 data type");
return false;
}
template<typename ... Params>
bool FalseInputFuncF32(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with float32 data type input");
return false;
}
template<typename ... Params>
bool FalseInputFuncF16(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with float16 data type input");
return false;
}
template<typename ... Params>
bool FalseOutputFuncF32(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with float32 data type output");
return false;
}
template<typename ... Params>
bool FalseOutputFuncF16(Optional<std::string&> reasonIfUnsupported, Params&&... params)
{
+ boost::ignore_unused(params...);
SetValueChecked(reasonIfUnsupported, "Layer is not supported with float16 data type output");
return false;
}
#include <boost/test/unit_test.hpp>
#include <boost/cast.hpp>
+#include <boost/core/ignore_unused.hpp>
#include <utility>
armnn::Graph& graph,
bool biasEnabled = false)
{
+ boost::ignore_unused(graph);
+
// To create a PreCompiled layer, create a network and Optimize it.
armnn::Network net;
struct SplitLastDimFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser>
{
SplitLastDimFixture(bool withDimZero=false) {
+ boost::ignore_unused(withDimZero);
m_Prototext = R"(
node {
name: "Placeholder"
const unsigned int firstAxisInclusive,
const unsigned int lastAxisExclusive)
{
- BOOST_ASSERT(0 <= firstAxisInclusive);
BOOST_ASSERT(firstAxisInclusive <= lastAxisExclusive);
BOOST_ASSERT(lastAxisExclusive <= shape.GetNumDimensions());
unsigned int count = 1;
unsigned int GetNumElementsAfter(const armnn::TensorShape& shape, unsigned int axis)
{
unsigned int numDim = shape.GetNumDimensions();
- BOOST_ASSERT(0 >= axis);
BOOST_ASSERT(axis <= numDim - 1);
unsigned int count = 1;
for (unsigned int i = axis; i < numDim; i++)
return CreateComparison(comparisonDescriptor, info);
}
-std::unique_ptr<IWorkload> ClWorkloadFactory::CreateFakeQuantization(
- const FakeQuantizationQueueDescriptor& descriptor,
- const WorkloadInfo& info) const
-{
- return MakeWorkload<NullWorkload, NullWorkload>(descriptor, info);
-}
-
std::unique_ptr<IWorkload> ClWorkloadFactory::CreateFloor(const FloorQueueDescriptor& descriptor,
const WorkloadInfo& info) const
{
std::unique_ptr<IWorkload> CreateEqual(const EqualQueueDescriptor& descriptor,
const WorkloadInfo& info) const override;
- std::unique_ptr<IWorkload> CreateFakeQuantization(const FakeQuantizationQueueDescriptor& descriptor,
- const WorkloadInfo& info) const override;
-
std::unique_ptr<IWorkload> CreateFloor(const FloorQueueDescriptor& descriptor,
const WorkloadInfo& info) const override;
return CreateComparison(comparisonDescriptor, info);
}
-std::unique_ptr<IWorkload> NeonWorkloadFactory::CreateFakeQuantization(
- const FakeQuantizationQueueDescriptor& descriptor,
- const WorkloadInfo& info) const
-{
- return nullptr;
-}
-
std::unique_ptr<IWorkload> NeonWorkloadFactory::CreateFloor(const FloorQueueDescriptor& descriptor,
const WorkloadInfo& info) const
{
descriptor, info, m_MemoryManager->GetIntraLayerManager());
}
-std::unique_ptr<IWorkload> NeonWorkloadFactory::CreateSpaceToBatchNd(const SpaceToBatchNdQueueDescriptor& descriptor,
- const WorkloadInfo& info) const
-{
- return nullptr;
-}
-
std::unique_ptr<IWorkload> NeonWorkloadFactory::CreateSpaceToDepth(
const armnn::SpaceToDepthQueueDescriptor& descriptor, const armnn::WorkloadInfo& info) const
{
std::unique_ptr<IWorkload> CreateEqual(const EqualQueueDescriptor& descriptor,
const WorkloadInfo& info) const override;
- std::unique_ptr<IWorkload> CreateFakeQuantization(const FakeQuantizationQueueDescriptor& descriptor,
- const WorkloadInfo& info) const override;
-
std::unique_ptr<IWorkload> CreateFloor(const FloorQueueDescriptor& descriptor,
const WorkloadInfo& info) const override;
std::unique_ptr<IWorkload> CreateSoftmax(const SoftmaxQueueDescriptor& descriptor,
const WorkloadInfo& info) const override;
- std::unique_ptr<IWorkload> CreateSpaceToBatchNd(const SpaceToBatchNdQueueDescriptor& descriptor,
- const WorkloadInfo& info) const override;
-
std::unique_ptr<IWorkload> CreateSpaceToDepth(const SpaceToDepthQueueDescriptor& descriptor,
const WorkloadInfo& info) const override;
void RefMemoryManager::Pool::Acquire()
{
BOOST_ASSERT_MSG(!m_Pointer, "RefMemoryManager::Pool::Acquire() called when memory already acquired");
- BOOST_ASSERT(m_Size >= 0);
m_Pointer = ::operator new(size_t(m_Size));
}
#include "DeepSpeechV1Database.hpp"
#include <boost/assert.hpp>
+#include <boost/core/ignore_unused.hpp>
#include <boost/numeric/conversion/cast.hpp>
#include <boost/test/tools/floating_point_comparison.hpp>
TestCaseResult ProcessResult(const InferenceTestOptions& options) override
{
+ boost::ignore_unused(options);
const std::vector<float>& output1 = boost::get<std::vector<float>>(this->GetOutputs()[0]); // logits
BOOST_ASSERT(output1.size() == k_OutputSize1);