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author | Matthew Sloyan <matthew.sloyan@arm.com> | 2020-09-11 16:17:48 +0100 |
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committer | Narumol Prangnawarat <narumol.prangnawarat@arm.com> | 2020-09-14 17:14:30 +0000 |
commit | 589e3e81a86c83456580e112978bf7a0ed5f43ac (patch) | |
tree | 0b273313f7bb8fd34696abd129bd3402d737ef4a /src/armnnTfLiteParser/TfLiteParser.cpp | |
parent | 04a729708f986b1a69c1efc42d5cf18271cfae1e (diff) | |
download | armnn-589e3e81a86c83456580e112978bf7a0ed5f43ac.tar.gz |
IVGCVSW-5302 Remove some boost::numeric_cast from parsers
* Replaced with armnn/utility/NumericCast.hpp
* Exclusions in armnnCaffeParser
* Three excluded as requires float implementation in NumericCast.hpp
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: Ib468b606238694334a8319d0ed5db381ce37a915
Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
-rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 23 |
1 files changed, 11 insertions, 12 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index 8bc475347c..109c2c2be1 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -28,7 +28,6 @@ #include <flatbuffers/flexbuffers.h> #include <boost/format.hpp> -#include <boost/numeric/conversion/cast.hpp> #include <fstream> #include <algorithm> @@ -388,10 +387,10 @@ armnn::TensorInfo ToTensorInfo(TfLiteParser::TensorRawPtr tensorPtr, { // NOTE: we lose precision here when converting from 64 bit to 32 // but this is what we support at the moment in ArmNN - quantizationOffset = boost::numeric_cast<int32_t>(tensorPtr->quantization->zero_point[0]); + quantizationOffset = armnn::numeric_cast<int32_t>(tensorPtr->quantization->zero_point[0]); } - TensorShape tensorShape(boost::numeric_cast<unsigned int>(safeShape.size()), + TensorShape tensorShape(armnn::numeric_cast<unsigned int>(safeShape.size()), safeShape.data()); if (isDynamic) { @@ -414,7 +413,7 @@ armnn::TensorInfo ToTensorInfo(TfLiteParser::TensorRawPtr tensorPtr, std::back_inserter(quantizationScales)); // QSymmS8 Per-axis - TensorShape tensorShape(boost::numeric_cast<unsigned int>(safeShape.size()), + TensorShape tensorShape(armnn::numeric_cast<unsigned int>(safeShape.size()), safeShape.data()); if (isDynamic) { @@ -423,14 +422,14 @@ armnn::TensorInfo ToTensorInfo(TfLiteParser::TensorRawPtr tensorPtr, armnn::TensorInfo result(tensorShape, type, quantizationScales, - dimensionMappings[boost::numeric_cast<unsigned int>( + dimensionMappings[armnn::numeric_cast<unsigned int>( tensorPtr->quantization->quantized_dimension)]); return result; } } else { - TensorShape tensorShape(boost::numeric_cast<unsigned int>(safeShape.size()), + TensorShape tensorShape(armnn::numeric_cast<unsigned int>(safeShape.size()), safeShape.data()); if (isDynamic) { @@ -866,8 +865,8 @@ void TfLiteParser::ParseUnsupportedOperator(size_t subgraphIndex, size_t operato auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); - const unsigned int numInputs = boost::numeric_cast<unsigned int>(inputs.size()); - const unsigned int numOutputs = boost::numeric_cast<unsigned int>(outputs.size()); + const unsigned int numInputs = armnn::numeric_cast<unsigned int>(inputs.size()); + const unsigned int numOutputs = armnn::numeric_cast<unsigned int>(outputs.size()); StandInDescriptor descriptor(numInputs, numOutputs); auto layerName = boost::str(boost::format("StandIn:%1%:%2%:%3%") % subgraphIndex % operatorIndex % opcode); @@ -2144,7 +2143,7 @@ armnn::TensorInfo TfLiteParser::OutputShapeOfReshape(const armnn::TensorInfo & i } auto targetNumElements = - boost::numeric_cast<unsigned int>( + armnn::numeric_cast<unsigned int>( std::accumulate(targetDimsIn.begin(), targetDimsIn.end(), -1, std::multiplies<int32_t>())); auto stretchIndex = static_cast<size_t>(std::distance(targetDimsIn.begin(), stretchDim)); @@ -2899,14 +2898,14 @@ void TfLiteParser::ParseSplitV(size_t subgraphIndex, size_t operatorIndex) // Check for inferred Axis if (numInferred == 0) { - if (splitSum != numeric_cast<int>(inputTensorInfo.GetShape()[splitDim])) + if (splitSum != armnn::numeric_cast<int>(inputTensorInfo.GetShape()[splitDim])) { throw ParseException("SplitV split_sizes does not sum to the dimension of value along split_dim."); } } else if (numInferred == 1) { - splitsData[inferIdx] = numeric_cast<int>(inputTensorInfo.GetShape()[splitDim]) - splitSum; + splitsData[inferIdx] = armnn::numeric_cast<int>(inputTensorInfo.GetShape()[splitDim]) - splitSum; } else { @@ -2922,7 +2921,7 @@ void TfLiteParser::ParseSplitV(size_t subgraphIndex, size_t operatorIndex) unsigned int accumSplit = 0; for (unsigned int j = 0; j < numSplits; ++j) { - unsigned int splitSize = numeric_cast<unsigned int>(splitsData[j]); + unsigned int splitSize = armnn::numeric_cast<unsigned int>(splitsData[j]); // Set the size of the views. for (unsigned int dimIdx = 0; dimIdx < inputTensorInfo.GetNumDimensions(); ++dimIdx) |