IVGCVSW-4246 Clean build of parsers with -Wextra
Change-Id: Ib00f185b431ab74fd9425d8f478bd2ddb182f74b
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 6853512..9c7dda8 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -385,6 +385,7 @@
armnn::TensorInfo& tensorInfo,
armnn::Optional<armnn::PermutationVector&> permutationVector)
{
+ boost::ignore_unused(tensorPtr);
BOOST_ASSERT_MSG(tensorPtr != nullptr, "tensorPtr is null");
BOOST_ASSERT_MSG(bufferPtr != nullptr,
boost::str(
diff --git a/src/armnnTfLiteParser/test/Unsupported.cpp b/src/armnnTfLiteParser/test/Unsupported.cpp
index 25abde8..9a9cdc5 100644
--- a/src/armnnTfLiteParser/test/Unsupported.cpp
+++ b/src/armnnTfLiteParser/test/Unsupported.cpp
@@ -33,7 +33,7 @@
void VisitInputLayer(const IConnectableLayer*, LayerBindingId, const char*) override {}
- void VisitOutputLayer(const IConnectableLayer*, LayerBindingId id, const char*) override {}
+ void VisitOutputLayer(const IConnectableLayer*, LayerBindingId, const char*) override {}
void VisitStandInLayer(const IConnectableLayer* layer,
const StandInDescriptor& descriptor,
diff --git a/src/armnnTfParser/TfParser.cpp b/src/armnnTfParser/TfParser.cpp
index 8c68659..ca98f46 100755
--- a/src/armnnTfParser/TfParser.cpp
+++ b/src/armnnTfParser/TfParser.cpp
@@ -17,7 +17,7 @@
#include <google/protobuf/io/zero_copy_stream_impl.h>
#include <google/protobuf/text_format.h>
-#include "tensorflow/core/framework/graph.pb.h"
+#include <tensorflow/core/framework/graph.pb.h>
#include <boost/format.hpp>
#include <boost/core/ignore_unused.hpp>
@@ -727,6 +727,7 @@
ParsedTfOperationPtr TfParser::ParseAddN(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
uint32_t numberOfInputs = ReadMandatoryNodeUint32Attribute(nodeDef, "N");
if (numberOfInputs < 2)
{
@@ -806,6 +807,7 @@
ParsedTfOperationPtr TfParser::ParseAdd(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
// If one of the inputs is a MatMul and the other is a const, then we handle both nodes
@@ -835,6 +837,7 @@
ParsedTfOperationPtr TfParser::ParseBiasAdd(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
return AddAdditionLayer(nodeDef, true);
}
@@ -865,6 +868,7 @@
ParsedTfOperationPtr TfParser::ParseIdentity(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 1);
// Any requests for the output slots of this node should be forwarded to the node connected as input.
return std::make_unique<ParsedIdentityTfOperation>(this, nodeDef, inputs[0].m_IndexedValue);
@@ -1058,6 +1062,7 @@
ParsedTfOperationPtr TfParser::ParseConst(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
BOOST_ASSERT(nodeDef.op() == "Const");
if (nodeDef.attr().count("value") == 0)
@@ -1194,6 +1199,7 @@
ParsedTfOperationPtr TfParser::ParseConv2D(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
IOutputSlot& inputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
TensorInfo inputTensorInfo = inputSlot.GetTensorInfo();
@@ -1335,6 +1341,7 @@
ParsedTfOperationPtr TfParser::ParseDepthwiseConv2D(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
IOutputSlot& inputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
TensorInfo inputTensorInfo = inputSlot.GetTensorInfo();
@@ -1530,6 +1537,7 @@
ParsedTfOperationPtr TfParser::ParseExpandDims(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 1);
IOutputSlot& prevLayerOutputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
@@ -1550,6 +1558,7 @@
ParsedTfOperationPtr TfParser::ParseFusedBatchNorm(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 5);
if (!HasParsedConstTensor<float>(inputs[1].m_IndexedValue->GetNode().name()))
@@ -1698,6 +1707,7 @@
ParsedTfOperationPtr TfParser::ParseMaximum(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
if (inputs.size() != 2)
{
@@ -1835,6 +1845,7 @@
ParsedTfOperationPtr TfParser::ParseGather(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
IOutputSlot& params = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
IOutputSlot& indices = inputs[1].m_IndexedValue->ResolveArmnnOutputSlot(inputs[1].m_Index);
@@ -1871,6 +1882,7 @@
ParsedTfOperationPtr TfParser::ParseGreater(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::pair<armnn::IOutputSlot*, armnn::IOutputSlot*> inputLayers = ProcessElementwiseInputSlots(nodeDef, "Greater");
IOutputSlot* input0Slot = inputLayers.first;
IOutputSlot* input1Slot = inputLayers.second;
@@ -1884,6 +1896,7 @@
ParsedTfOperationPtr TfParser::ParseEqual(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::pair<armnn::IOutputSlot*, armnn::IOutputSlot*> inputLayers = ProcessElementwiseInputSlots(nodeDef, "Equal");
IOutputSlot* input0Slot = inputLayers.first;
IOutputSlot* input1Slot = inputLayers.second;
@@ -1897,6 +1910,7 @@
ParsedTfOperationPtr TfParser::ParseMinimum(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::pair<armnn::IOutputSlot*, armnn::IOutputSlot*> inputLayers = ProcessElementwiseInputSlots(nodeDef, "Minimum");
IOutputSlot* input0Slot = inputLayers.first;
IOutputSlot* input1Slot = inputLayers.second;
@@ -1908,6 +1922,7 @@
ParsedTfOperationPtr TfParser::ParseSub(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
IOutputSlot* input0Slot = &inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
@@ -1999,6 +2014,7 @@
ParsedTfOperationPtr TfParser::ParsePad(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
// input consists of:
// input[0] the tensor which will be padded
// input[1] the tensor holding the padding values
@@ -2073,6 +2089,7 @@
ParsedTfOperationPtr TfParser::ParseConcat(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfConstNodeDef> nodes = GetTfInputNodes(nodeDef);
// In tensorflow, we have the last input of the Concat layer as the axis for concatenation.
@@ -2158,6 +2175,7 @@
ParsedTfOperationPtr TfParser::ParseShape(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
// Note: the Shape layer is handled in a special way, because:
// 1. ARMNN doesn't support int32 tensors which it outputs.
// 2. ARMNN works with statically shaped tensors which are known at parse time.
@@ -2200,6 +2218,7 @@
ParsedTfOperationPtr TfParser::ParseReshape(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
ParsedTfOperation* inputNode = inputs[0].m_IndexedValue;
@@ -2238,6 +2257,7 @@
ParsedTfOperationPtr TfParser::ParseResizeBilinear(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
if (!HasParsedConstTensor<int32_t>(inputs[1].m_IndexedValue->GetNode().name()))
@@ -2376,6 +2396,7 @@
ParsedTfOperationPtr TfParser::ParseSqueeze(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 1);
IOutputSlot& prevLayerOutputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
@@ -2395,6 +2416,7 @@
ParsedTfOperationPtr TfParser::ParseLrn(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 1);
NormalizationDescriptor normalizationDescriptor;
@@ -2440,12 +2462,15 @@
ParsedTfOperationPtr TfParser::ParseMatMul(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
+
// Defers the creation of the layer (see ParsedMatMulTfOperation).
return std::make_unique<ParsedMatMulTfOperation>(this, nodeDef);
}
ParsedTfOperationPtr TfParser::ParseMean(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
{
+ boost::ignore_unused(graphDef);
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 2);
IOutputSlot& inputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
TensorInfo inputTensorInfo = inputSlot.GetTensorInfo();
@@ -2484,7 +2509,7 @@
std::inserter(positiveAxisSet, positiveAxisSet.begin()),
[rank](int i) -> unsigned int { return static_cast<unsigned int>((i + rank) % rank); });
- CalculateReducedOutputTensoInfo(inputTensorInfo, axisTensorInfo, positiveAxisSet, keepDims, outputTensorInfo);
+ CalculateReducedOutputTensoInfo(inputTensorInfo, positiveAxisSet, keepDims, outputTensorInfo);
if (inputTensorInfo.GetNumDimensions() > positiveAxisSet.size())
{
@@ -2774,6 +2799,8 @@
ParsedTfOperationPtr TfParser::ParsePooling2d(const tensorflow::NodeDef& nodeDef,
const tensorflow::GraphDef& graphDef, PoolingAlgorithm pooltype)
{
+ boost::ignore_unused(graphDef);
+
std::vector<OutputOfParsedTfOperation> inputs = GetInputParsedTfOperationsChecked(nodeDef, 1);
IOutputSlot& inputSlot = inputs[0].m_IndexedValue->ResolveArmnnOutputSlot(inputs[0].m_Index);
TensorInfo inputTensorInfo = inputSlot.GetTensorInfo();
diff --git a/src/armnnUtils/ParserHelper.cpp b/src/armnnUtils/ParserHelper.cpp
index 990a9b2..88e5756 100644
--- a/src/armnnUtils/ParserHelper.cpp
+++ b/src/armnnUtils/ParserHelper.cpp
@@ -51,8 +51,9 @@
}
}
-void CalculateReducedOutputTensoInfo(const armnn::TensorInfo& inputTensorInfo, const armnn::TensorInfo& axisTensorInfo,
- const std::set<unsigned int>& axisSet, bool keepDims,
+void CalculateReducedOutputTensoInfo(const armnn::TensorInfo& inputTensorInfo,
+ const std::set<unsigned int>& axisSet,
+ bool keepDims,
armnn::TensorInfo& outputTensorInfo)
{
std::vector<unsigned int> outputShapeVector;
diff --git a/src/armnnUtils/ParserHelper.hpp b/src/armnnUtils/ParserHelper.hpp
index bcc1e5b..d85ce26 100644
--- a/src/armnnUtils/ParserHelper.hpp
+++ b/src/armnnUtils/ParserHelper.hpp
@@ -17,8 +17,9 @@
unsigned int& mergeDimOrigin);
/// Creates a tensor info after reducing the dimensions mentioned in axisData.
-void CalculateReducedOutputTensoInfo(const armnn::TensorInfo& inputTensorInfo, const armnn::TensorInfo& axisTensorInfo,
- const std::set<unsigned int>& axisSet, bool keepDims,
+void CalculateReducedOutputTensoInfo(const armnn::TensorInfo& inputTensorInfo,
+ const std::set<unsigned int>& axisSet,
+ bool keepDims,
armnn::TensorInfo& outputTensorInfo);
} // namespace armnnUtils
diff --git a/src/armnnUtils/test/ParserHelperTest.cpp b/src/armnnUtils/test/ParserHelperTest.cpp
index 122ad76..636e2bd 100644
--- a/src/armnnUtils/test/ParserHelperTest.cpp
+++ b/src/armnnUtils/test/ParserHelperTest.cpp
@@ -22,54 +22,39 @@
TensorInfo inputTensorInfo(3, &inputShape[0], DataType::Float32);
// Reducing all dimensions results in one single output value (one dimension)
- unsigned int axisShape1[] = { 3 };
std::set<unsigned int> axisData1 = { 0, 1, 2 };
- TensorInfo axisTensorInfo1(1, &axisShape1[0], DataType::Signed32);
-
TensorInfo outputTensorInfo1;
- CalculateReducedOutputTensoInfo(inputTensorInfo, axisTensorInfo1, axisData1,
- keepDims, outputTensorInfo1);
+ CalculateReducedOutputTensoInfo(inputTensorInfo, axisData1, keepDims, outputTensorInfo1);
BOOST_ASSERT(outputTensorInfo1.GetNumDimensions() == 1);
BOOST_ASSERT(outputTensorInfo1.GetShape()[0] == 1);
// Reducing dimension 0 results in a 3x4 size tensor (one dimension)
- unsigned int axisShape2[] = { 1 };
std::set<unsigned int> axisData2 = { 0 };
- TensorInfo axisTensorInfo2(1, &axisShape2[0], DataType::Signed32);
-
TensorInfo outputTensorInfo2;
- CalculateReducedOutputTensoInfo(inputTensorInfo, axisTensorInfo2, axisData2,
- keepDims, outputTensorInfo2);
+ CalculateReducedOutputTensoInfo(inputTensorInfo, axisData2, keepDims, outputTensorInfo2);
BOOST_ASSERT(outputTensorInfo2.GetNumDimensions() == 1);
BOOST_ASSERT(outputTensorInfo2.GetShape()[0] == 12);
// Reducing dimensions 0,1 results in a 4 size tensor (one dimension)
- unsigned int axisShape3[] = { 2 };
std::set<unsigned int> axisData3 = { 0, 1 };
- TensorInfo axisTensorInfo3(1, &axisShape3[0], DataType::Signed32);
-
TensorInfo outputTensorInfo3;
- CalculateReducedOutputTensoInfo(inputTensorInfo, axisTensorInfo3, axisData3,
- keepDims, outputTensorInfo3);
+ CalculateReducedOutputTensoInfo(inputTensorInfo, axisData3, keepDims, outputTensorInfo3);
BOOST_ASSERT(outputTensorInfo3.GetNumDimensions() == 1);
BOOST_ASSERT(outputTensorInfo3.GetShape()[0] == 4);
// Reducing dimension 0 results in a { 1, 3, 4 } dimension tensor
keepDims = true;
- unsigned int axisShape4[] = { 1 };
std::set<unsigned int> axisData4 = { 0 };
- TensorInfo axisTensorInfo4(1, &axisShape4[0], DataType::Signed32);
TensorInfo outputTensorInfo4;
- CalculateReducedOutputTensoInfo(inputTensorInfo, axisTensorInfo4, axisData4,
- keepDims, outputTensorInfo4);
+ CalculateReducedOutputTensoInfo(inputTensorInfo, axisData4, keepDims, outputTensorInfo4);
BOOST_ASSERT(outputTensorInfo4.GetNumDimensions() == 3);
BOOST_ASSERT(outputTensorInfo4.GetShape()[0] == 1);
@@ -78,14 +63,11 @@
// Reducing dimension 1, 2 results in a { 2, 1, 1 } dimension tensor
keepDims = true;
- unsigned int axisShape5[] = { 2 };
std::set<unsigned int> axisData5 = { 1, 2 };
- TensorInfo axisTensorInfo5(1, &axisShape5[0], DataType::Signed32);
TensorInfo outputTensorInfo5;
- CalculateReducedOutputTensoInfo(inputTensorInfo, axisTensorInfo5, axisData5,
- keepDims, outputTensorInfo5);
+ CalculateReducedOutputTensoInfo(inputTensorInfo, axisData5, keepDims, outputTensorInfo5);
BOOST_ASSERT(outputTensorInfo5.GetNumDimensions() == 3);
BOOST_ASSERT(outputTensorInfo5.GetShape()[0] == 2);
diff --git a/src/backends/neon/NeonLayerSupport.cpp b/src/backends/neon/NeonLayerSupport.cpp
index c79aa78..a73837b 100644
--- a/src/backends/neon/NeonLayerSupport.cpp
+++ b/src/backends/neon/NeonLayerSupport.cpp
@@ -69,7 +69,7 @@
template< typename ... Args>
bool IsNeonBackendSupported(Optional<std::string&> reasonIfUnsupported, Args... args)
{
- boost::ignore_unused((args)...);
+ boost::ignore_unused(reasonIfUnsupported, (args)...);
#if defined(ARMCOMPUTENEON_ENABLED)
return true;
#else