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author | Derek Lamberti <derek.lamberti@arm.com> | 2019-12-10 22:00:43 +0000 |
---|---|---|
committer | Derek Lamberti <derek.lamberti@arm.com> | 2020-01-03 15:12:19 +0000 |
commit | baa177f0d465fe1d4f9e1979e1611ff6b1f128e0 (patch) | |
tree | 8eff0469fcff76cbad0d8e24b78859dec0e72822 /src/armnnTfParser | |
parent | f143fba6e617267ed33acc8b3e1eb2130de0ffe0 (diff) | |
download | armnn-baa177f0d465fe1d4f9e1979e1611ff6b1f128e0.tar.gz |
IVGCVSW-4246 Clean build of parsers with -Wextra
Change-Id: Ib00f185b431ab74fd9425d8f478bd2ddb182f74b
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>
Diffstat (limited to 'src/armnnTfParser')
-rwxr-xr-x | src/armnnTfParser/TfParser.cpp | 31 |
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(); |