diff options
Diffstat (limited to 'src/armnnTfLiteParser/TfLiteParser.cpp')
| -rw-r--r-- | src/armnnTfLiteParser/TfLiteParser.cpp | 64 |
1 files changed, 64 insertions, 0 deletions
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp index dd1f5773af..13e4604490 100644 --- a/src/armnnTfLiteParser/TfLiteParser.cpp +++ b/src/armnnTfLiteParser/TfLiteParser.cpp @@ -24,6 +24,7 @@ #include <fstream> #include <algorithm> #include <limits> +#include <numeric> using namespace armnn; using armnn::CheckLocation; @@ -457,6 +458,7 @@ TfLiteParser::TfLiteParser() m_ParserFunctions[tflite::BuiltinOperator_SQUEEZE] = &TfLiteParser::ParseSqueeze; m_ParserFunctions[tflite::BuiltinOperator_RELU] = &TfLiteParser::ParseRelu; m_ParserFunctions[tflite::BuiltinOperator_RELU6] = &TfLiteParser::ParseRelu6; + m_ParserFunctions[tflite::BuiltinOperator_RESHAPE] = &TfLiteParser::ParseReshape; } void TfLiteParser::ResetParser() @@ -1033,6 +1035,68 @@ void TfLiteParser::ParseRelu6(size_t subgraphIndex, size_t operatorIndex) RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); } +armnn::TensorInfo TfLiteParser::OutputShapeOfReshape(const armnn::TensorInfo & inputTensorInfo, + const std::vector<int32_t> & targetDimsIn) +{ + std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end()); + const auto stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1); + + if (stretchDim != targetDimsIn.end()) + { + if (std::find(std::next(stretchDim), targetDimsIn.end(), -1) != targetDimsIn.end()) + { + throw ParseException( + boost::str( + boost::format("At most one component of shape can be -1 %1%") % CHECK_LOCATION().AsString())); + } + + auto targetNumElements = + boost::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)); + outputDims[stretchIndex] = inputTensorInfo.GetNumElements() / targetNumElements; + } + + TensorShape outputShape = TensorShape(static_cast<unsigned int>(outputDims.size()), outputDims.data()); + + TensorInfo reshapeInfo = inputTensorInfo; + reshapeInfo.SetShape(outputShape); + + return reshapeInfo; +} + +void TfLiteParser::ParseReshape(size_t subgraphIndex, size_t operatorIndex) +{ + CHECK_MODEL(m_Model, subgraphIndex, operatorIndex); + + auto inputs = GetInputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + + auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + const auto & operatorPtr = m_Model->subgraphs[subgraphIndex]->operators[operatorIndex]; + const auto * options = operatorPtr->builtin_options.AsReshapeOptions(); + + armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); + armnn::TensorInfo outputTensorInfo = + TfLiteParser::OutputShapeOfReshape(inputTensorInfo, options->new_shape); + + ReshapeDescriptor reshapeDesc; + reshapeDesc.m_TargetShape = outputTensorInfo.GetShape(); + + auto layerName = boost::str(boost::format("Reshape:%1%:%2%") % subgraphIndex % operatorIndex); + IConnectableLayer* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str()); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]}); + + auto outputTensorIndexes = AsUnsignedVector(GetOutputTensorIds(m_Model, subgraphIndex, operatorIndex)); + RegisterOutputSlots(subgraphIndex, operatorIndex, layer, {outputTensorIndexes[0]}); +} + armnn::IConnectableLayer* TfLiteParser::AddFusedActivationLayer(armnn::IConnectableLayer* prevLayer, unsigned int outputSlot, tflite::ActivationFunctionType activationType) |