IVGCVSW-4246 Clean build of parsers with -Wextra

Change-Id: Ib00f185b431ab74fd9425d8f478bd2ddb182f74b
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>

1 files changed, 29 insertions, 2 deletions

diff --git a/src/armnnTfParser/TfParser.cpp b/src/armnnTfParser/TfParser.cpp
index 8c68659b95..ca98f463b5 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 @@ IConnectableLayer* TfParser::CreateAdditionLayer(
 
 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::ParseAddN(const tensorflow::NodeDef& nodeDef, con
 
 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::ParseAdd(const tensorflow::NodeDef& nodeDef, cons
 
 ParsedTfOperationPtr TfParser::ParseBiasAdd(const tensorflow::NodeDef& nodeDef, const tensorflow::GraphDef& graphDef)
 {
+    boost::ignore_unused(graphDef);
     return AddAdditionLayer(nodeDef, true);
 }
 
@@ -865,6 +868,7 @@ private:
 
 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 @@ struct InvokeParseFunction
 
 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 @@ unsigned int TfParser::GetConstInputIndex(const std::vector<OutputOfParsedTfOper
 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::ParseConv2D(const tensorflow::NodeDef& nodeDef,
 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 @@ TensorInfo OutputShapeOfExpandDims(const tensorflow::NodeDef& nodeDef, TensorInf
 
 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::ParseExpandDims(const tensorflow::NodeDef& nodeDe
 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 @@ bool TfParser::IsSupportedLeakyReluPattern(const tensorflow::NodeDef& mulNodeDef
 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::ProcessElementwiseLayer(
 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::ParseGather(const tensorflow::NodeDef& nodeDef,
 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::ParseGreater(const tensorflow::NodeDef& nodeDef,
 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::ParseEqual(const tensorflow::NodeDef& nodeDef,
 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::ParseMinimum(const tensorflow::NodeDef& nodeDef,
 
 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 @@ TensorInfo CalculatePaddedOutputTensorInfo(const TensorInfo& inputTensorInfo,
 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::ParsePad(const tensorflow::NodeDef& nodeDef,
 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::ParseConcat(const tensorflow::NodeDef& nodeDef,
 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::ParseShape(const tensorflow::NodeDef& nodeDef,
 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::ParseReshape(const tensorflow::NodeDef& nodeDef,
 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 @@ TensorInfo OutputShapeOfSqueeze(const tensorflow::NodeDef& nodeDef, TensorInfo i
 
 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::ParseSqueeze(const tensorflow::NodeDef& nodeDef,
 
 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 @@ public:
 
 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 @@ ParsedTfOperationPtr TfParser::ParseMean(const tensorflow::NodeDef& nodeDef, con
                    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::ParseAvgPool(const tensorflow::NodeDef& nodeDef,
 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();