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author | Derek Lamberti <derek.lamberti@arm.com> | 2019-02-20 13:57:42 +0000 |
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committer | Derek Lamberti <derek.lamberti@arm.com> | 2019-02-20 15:41:32 +0000 |
commit | 0028d1b0ce5f4c2c6a6eb3c66f38111c21eb47a3 (patch) | |
tree | 894d7ac05ef1610bad636e24489248e6c472b313 /src/armnnDeserializeParser/DeserializeParser.cpp | |
parent | be25fc18f7e55bc39f537601e42a9d5c9d0c111f (diff) | |
download | armnn-0028d1b0ce5f4c2c6a6eb3c66f38111c21eb47a3.tar.gz |
IVGSVSW-2736 Rename DeserializeParser => Deserializer & fix namespaces
Change-Id: I4166c0bbb5ba7f8b8884e71134c21f43d1fc27b0
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>
Diffstat (limited to 'src/armnnDeserializeParser/DeserializeParser.cpp')
-rw-r--r-- | src/armnnDeserializeParser/DeserializeParser.cpp | 984 |
1 files changed, 0 insertions, 984 deletions
diff --git a/src/armnnDeserializeParser/DeserializeParser.cpp b/src/armnnDeserializeParser/DeserializeParser.cpp deleted file mode 100644 index 9b6b5b9473..0000000000 --- a/src/armnnDeserializeParser/DeserializeParser.cpp +++ /dev/null @@ -1,984 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "DeserializeParser.hpp" - -#include <armnn/ArmNN.hpp> -#include <armnn/Exceptions.hpp> - -#include <ParserHelper.hpp> -#include <Permute.hpp> -#include <VerificationHelpers.hpp> - -#include <boost/filesystem.hpp> -#include <boost/format.hpp> -#include <boost/core/ignore_unused.hpp> -#include <boost/assert.hpp> -#include <boost/format.hpp> -#include <boost/log/trivial.hpp> - -// The generated code based on the Serialize schema: -#include <Schema_generated.h> - -#include <fstream> -#include <algorithm> -#include <limits> -#include <numeric> - -using armnn::ParseException; -using namespace armnn; -using namespace armnn::armnnSerializer; - -namespace armnnDeserializeParser -{ - -namespace -{ - -const uint32_t VIRTUAL_LAYER_ID = std::numeric_limits<uint32_t>::max(); - - void CheckGraph(const DeserializeParser::GraphPtr& graph, - unsigned int layersIndex, - const CheckLocation& location) -{ - if (graph->layers() == nullptr) - { - throw ParseException( - boost::str( - boost::format("%1% was called with invalid (null) graph. " - "Possible reason is that the graph is not yet loaded and Unpack(ed). " - "layers:%2% at %3%") % - location.m_Function % - layersIndex % - location.FileLine())); - } - else if (layersIndex >= graph->layers()->size()) - { - throw ParseException( - boost::str( - boost::format("%1% was called with an invalid layers index. " - "layers:%2% at %3%") % - location.m_Function % - layersIndex % - location.FileLine())); - } -} - -void CheckLayers(const DeserializeParser::GraphPtr& graph, - unsigned int layersIndex, - unsigned int layerIndex, - const CheckLocation& location) -{ - if (graph->layers() == nullptr) - { - throw ParseException( - boost::str( - boost::format("%1% was called with invalid (null) graph. " - "Possible reason is that the graph is not yet loaded and Unpack(ed). " - "layers:%2% at %3%") % - location.m_Function % - layersIndex % - location.FileLine())); - } - else if (layersIndex >= graph->layers()->size()) - { - throw ParseException( - boost::str( - boost::format("%1% was called with an invalid layers index. " - "layers:%2% at %3%") % - location.m_Function % - layersIndex % - location.FileLine())); - } - else if (layerIndex >= graph->layers()[layersIndex].size() - && layerIndex != VIRTUAL_LAYER_ID) - { - throw ParseException( - boost::str( - boost::format("%1% was called with an invalid layer index. " - "layers:%2% layer:%3% at %4%") % - location.m_Function % - layersIndex % - layerIndex % - location.FileLine())); - } -} - -void CheckTensorPtr(DeserializeParser::TensorRawPtr rawPtr, - const CheckLocation& location) -{ - if (rawPtr == nullptr) - { - throw ParseException( - boost::str( - boost::format("%1% was called with a null tensor pointer. " - "at %2%") % - location.m_Function % - location.FileLine())); - - } -} - -void CheckConstTensorPtr(DeserializeParser::ConstTensorRawPtr rawPtr, - const CheckLocation& location) -{ - if (rawPtr == nullptr) - { - throw ParseException(boost::str(boost::format("%1% was called with a null const tensor pointer. at %2%") % - location.m_Function % - location.FileLine())); - } -} - -#define CHECK_TENSOR_PTR(TENSOR_PTR) \ - CheckTensorPtr(TENSOR_PTR, CHECK_LOCATION()) - -#define CHECK_CONST_TENSOR_PTR(TENSOR_PTR) \ - CheckConstTensorPtr(TENSOR_PTR, CHECK_LOCATION()) - -#define CHECK_LAYERS(GRAPH, LAYERS_INDEX, LAYER_INDEX) \ - CheckLayers(GRAPH, LAYERS_INDEX, LAYER_INDEX, CHECK_LOCATION()) - -#define CHECK_GRAPH(GRAPH, LAYERS_INDEX) \ - CheckGraph(GRAPH, LAYERS_INDEX, CHECK_LOCATION()) -} - -bool CheckShape(const armnn::TensorShape& actual, const std::vector<uint32_t>& expected) -{ - const unsigned int actualSize = actual.GetNumDimensions(); - if (actualSize != expected.size()) - { - return false; - } - - for (unsigned int i = 0u; i < actualSize; i++) - { - if (actual[i] != static_cast<unsigned int>(expected[i])) - { - return false; - } - } - - return true; -} - -DeserializeParser::DeserializeParser() -: m_Network(nullptr, nullptr), -//May require LayerType_Max to be included -m_ParserFunctions(Layer_MAX+1, &DeserializeParser::ParseUnsupportedLayer) -{ - // register supported layers - m_ParserFunctions[Layer_AdditionLayer] = &DeserializeParser::ParseAdd; - m_ParserFunctions[Layer_Convolution2dLayer] = &DeserializeParser::ParseConvolution2d; - m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &DeserializeParser::ParseDepthwiseConvolution2d; - m_ParserFunctions[Layer_MultiplicationLayer] = &DeserializeParser::ParseMultiplication; - m_ParserFunctions[Layer_Pooling2dLayer] = &DeserializeParser::ParsePooling2d; - m_ParserFunctions[Layer_ReshapeLayer] = &DeserializeParser::ParseReshape; - m_ParserFunctions[Layer_SoftmaxLayer] = &DeserializeParser::ParseSoftmax; -} - -DeserializeParser::LayerBaseRawPtr DeserializeParser::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex) -{ - auto layerType = graphPtr->layers()->Get(layerIndex)->layer_type(); - - switch(layerType) - { - case Layer::Layer_AdditionLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base(); - case Layer::Layer_Convolution2dLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_Convolution2dLayer()->base(); - case Layer::Layer_DepthwiseConvolution2dLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer()->base(); - case Layer::Layer_InputLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base(); - case Layer::Layer_MultiplicationLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base(); - case Layer::Layer_OutputLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base(); - case Layer::Layer_Pooling2dLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->base(); - case Layer::Layer_ReshapeLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base(); - case Layer::Layer_SoftmaxLayer: - return graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base(); - case Layer::Layer_NONE: - default: - throw ParseException(boost::str( - boost::format("Layer must have a type %1%") % - Layer::Layer_NONE)); - } -} - -int32_t DeserializeParser::GetBindingLayerInfo(const GraphPtr& graphPtr, unsigned int layerIndex) -{ - auto layerType = graphPtr->layers()->Get(layerIndex)->layer_type(); - - if (layerType == Layer::Layer_InputLayer) - { - return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->layerBindingId(); - } - else if ( layerType == Layer::Layer_OutputLayer ) - { - return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->layerBindingId(); - } - return 0; -} - -armnn::DataLayout ToDataLayout(armnn::armnnSerializer::DataLayout dataLayout) -{ - switch (dataLayout) - { - case armnn::armnnSerializer::DataLayout::DataLayout_NHWC: - return armnn::DataLayout::NHWC; - case armnn::armnnSerializer::DataLayout::DataLayout_NCHW: - default: - return armnn::DataLayout::NCHW; - } -} - -armnn::TensorInfo ToTensorInfo(DeserializeParser::TensorRawPtr tensorPtr) -{ - armnn::DataType type; - CHECK_TENSOR_PTR(tensorPtr); - - switch (tensorPtr->dataType()) - { - case DataType_QuantisedAsymm8: - type = armnn::DataType::QuantisedAsymm8; - break; - case DataType_Signed32: - type = armnn::DataType::Signed32; - break; - case DataType_Float32: - type = armnn::DataType::Float32; - break; - case DataType_Float16: - type = armnn::DataType::Float16; - break; - case DataType_Boolean: - type = armnn::DataType::Boolean; - break; - default: - { - CheckLocation location = CHECK_LOCATION(); - throw ParseException( - boost::str( - boost::format("Unsupported data type %1% = %2%. %3%") % - tensorPtr->dataType() % - EnumNameDataType(tensorPtr->dataType()) % - location.AsString())); - } - } - float quantizationScale = tensorPtr->quantizationScale(); - int32_t quantizationOffset = tensorPtr->quantizationOffset(); - - auto dimensions = tensorPtr->dimensions(); - unsigned int size = dimensions->size(); - std::vector<unsigned int> outputDims(dimensions->begin(), dimensions->begin() + size); - - // two statements (on purpose) for easier debugging: - armnn::TensorInfo result(size, - outputDims.data(), - type, - quantizationScale, - quantizationOffset); - return result; -} - -armnn::ConstTensor ToConstTensor(DeserializeParser::ConstTensorRawPtr constTensorPtr) -{ - CHECK_CONST_TENSOR_PTR(constTensorPtr); - armnn::TensorInfo tensorInfo = ToTensorInfo(constTensorPtr->info()); - - switch (constTensorPtr->data_type()) - { - case ConstTensorData_ByteData: - return armnn::ConstTensor(tensorInfo, constTensorPtr->data_as_ByteData()->data()->data()); - case ConstTensorData_ShortData: - return armnn::ConstTensor(tensorInfo, constTensorPtr->data_as_ShortData()->data()->data()); - case ConstTensorData_IntData: - return armnn::ConstTensor(tensorInfo, constTensorPtr->data_as_IntData()->data()->data()); - case ConstTensorData_LongData: - return armnn::ConstTensor(tensorInfo, constTensorPtr->data_as_LongData()->data()->data()); - default: - { - CheckLocation location = CHECK_LOCATION(); - throw ParseException( - boost::str(boost::format("Unsupported data type %1% = %2%. %3%") % - constTensorPtr->data_type() % - EnumNameConstTensorData(constTensorPtr->data_type()) % - location.AsString())); - } - } -} - -DeserializeParser::LayerBaseRawPtrVector DeserializeParser::GetGraphInputs(const GraphPtr& graphPtr) -{ - - CHECK_GRAPH(graphPtr, 0); - const auto& numInputs = graphPtr->inputIds()->size(); - - LayerBaseRawPtrVector result(numInputs); - - for (unsigned int i=0; i<numInputs; ++i) - { - uint32_t inputId = graphPtr->inputIds()->Get(i); - result[i] = GetBaseLayer(graphPtr, static_cast<uint32_t>(inputId)); - } - return result; -} - -DeserializeParser::LayerBaseRawPtrVector DeserializeParser::GetGraphOutputs(const GraphPtr& graphPtr) -{ - CHECK_GRAPH(graphPtr, 0); - const auto& numOutputs = graphPtr->outputIds()->size(); - LayerBaseRawPtrVector result(numOutputs); - - for (unsigned int i=0; i<numOutputs; ++i) - { - uint32_t outputId = graphPtr->outputIds()->Get(i); - - result[i] = GetBaseLayer(graphPtr, static_cast<uint32_t>(outputId)); - } - return result; -} - -DeserializeParser::TensorRawPtrVector DeserializeParser::GetInputs(const GraphPtr& graphPtr, - unsigned int layerIndex) -{ - CHECK_LAYERS(graphPtr, 0, layerIndex); - auto layer = GetBaseLayer(graphPtr, layerIndex); - const auto& numInputs = layer->inputSlots()->size(); - - TensorRawPtrVector result(numInputs); - - for (unsigned int i=0; i<numInputs; ++i) - { - auto inputId = CHECKED_NON_NEGATIVE(static_cast<int32_t> - (layer->inputSlots()->Get(i)->connection()->sourceLayerIndex())); - result[i] = GetBaseLayer(graphPtr, inputId)->outputSlots()->Get(0)->tensorInfo(); - } - return result; -} - -DeserializeParser::TensorRawPtrVector DeserializeParser::GetOutputs(const GraphPtr& graphPtr, - unsigned int layerIndex) -{ - CHECK_LAYERS(graphPtr, 0, layerIndex); - auto layer = GetBaseLayer(graphPtr, layerIndex); - const auto& numOutputs = layer->outputSlots()->size(); - - TensorRawPtrVector result(numOutputs); - - for (unsigned int i=0; i<numOutputs; ++i) - { - result[i] = layer->outputSlots()->Get(i)->tensorInfo(); - } - return result; -} - -void DeserializeParser::ParseUnsupportedLayer(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - const auto layerName = GetBaseLayer(m_Graph, layerIndex)->layerName()->c_str(); - throw ParseException( - boost::str( - boost::format("Layer not supported. " - "layerIndex: %1% " - "layerName: %2% / %3%") % - layerIndex % - layerName % - CHECK_LOCATION().AsString())); -} - -void DeserializeParser::ResetParser() -{ - m_Network = armnn::INetworkPtr(nullptr, nullptr); - m_Graph = nullptr; -} - -IDeserializeParser* IDeserializeParser::CreateRaw() -{ - return new DeserializeParser(); -} - -IDeserializeParserPtr IDeserializeParser::Create() -{ - return IDeserializeParserPtr(CreateRaw(), &IDeserializeParser::Destroy); -} - -void IDeserializeParser::Destroy(IDeserializeParser* parser) -{ - delete parser; -} - -INetworkPtr DeserializeParser::CreateNetworkFromBinary(const std::vector<uint8_t>& binaryContent) -{ - ResetParser(); - m_Graph = LoadGraphFromBinary(binaryContent.data(), binaryContent.size()); - return CreateNetworkFromGraph(); -} - -armnn::INetworkPtr DeserializeParser::CreateNetworkFromBinary(std::istream& binaryContent) -{ - ResetParser(); - m_Graph = LoadGraphFromBinary(binaryContent); - return CreateNetworkFromGraph(); -} - -DeserializeParser::GraphPtr DeserializeParser::LoadGraphFromBinary(const uint8_t* binaryContent, size_t len) -{ - if (binaryContent == nullptr) - { - throw InvalidArgumentException(boost::str(boost::format("Invalid (null) binary content %1%") % - CHECK_LOCATION().AsString())); - } - flatbuffers::Verifier verifier(binaryContent, len); - if (verifier.VerifyBuffer<SerializedGraph>() == false) - { - throw ParseException( - boost::str(boost::format("Buffer doesn't conform to the expected Armnn " - "flatbuffers format. size:%1% %2%") % - len % - CHECK_LOCATION().AsString())); - } - return GetSerializedGraph(binaryContent); -} - -DeserializeParser::GraphPtr DeserializeParser::LoadGraphFromBinary(std::istream& binaryContent) -{ - std::string content((std::istreambuf_iterator<char>(binaryContent)), std::istreambuf_iterator<char>()); - return GetSerializedGraph(content.data()); -} - -INetworkPtr DeserializeParser::CreateNetworkFromGraph() -{ - m_Network = INetwork::Create(); - BOOST_ASSERT(m_Graph != nullptr); - unsigned int layerIndex = 0; - m_GraphConnections.emplace_back(m_Graph->layers()->size()); - for (AnyLayer const* layer : *m_Graph->layers()) - { - if (layer->layer_type() != Layer_InputLayer && - layer->layer_type() != Layer_OutputLayer) - { - // lookup and call the parser function - auto& parserFunction = m_ParserFunctions[layer->layer_type()]; - (this->*parserFunction)(layerIndex); - } - ++layerIndex; - } - - SetupInputLayers(); - SetupOutputLayers(); - - // establish the connections from the layer outputs to the inputs of the subsequent layers - for (size_t connectionIndex = 0; connectionIndex < m_GraphConnections[0].size(); ++connectionIndex) - { - if (m_GraphConnections[0][connectionIndex].outputSlot != nullptr) - { - for (size_t inputSlotIdx = 0; - inputSlotIdx < m_GraphConnections[0][connectionIndex].inputSlots.size(); - ++inputSlotIdx) - { - m_GraphConnections[0][connectionIndex].outputSlot->Connect( - *(m_GraphConnections[0][connectionIndex].inputSlots[inputSlotIdx])); - } - } - } - - return std::move(m_Network); -} - -BindingPointInfo DeserializeParser::GetNetworkInputBindingInfo(unsigned int layerIndex, - const std::string& name) const -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto inputs = GetGraphInputs(m_Graph); - - for (auto const& input : inputs) - { - if (input->layerName()->c_str() == name) - { - int bindingId = reinterpret_cast<armnn::LayerBindingId>(GetBindingLayerInfo(m_Graph, input->index())); - auto layerBase = GetBaseLayer(m_Graph,input->index())->outputSlots()->Get(layerIndex); - return std::make_pair(bindingId, ToTensorInfo(layerBase->tensorInfo())); - } - } - throw ParseException( - boost::str( - boost::format("No input binding found for layer:%1% / %2%") % - name % - CHECK_LOCATION().AsString())); -} - -BindingPointInfo DeserializeParser::GetNetworkOutputBindingInfo(unsigned int layerIndex, - const std::string& name) const -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto outputs = GetGraphOutputs(m_Graph); - - for (auto const& output : outputs) - { - if (output->layerName()->c_str() == name) - { - int bindingId = reinterpret_cast<armnn::LayerBindingId>(GetBindingLayerInfo(m_Graph, output->index())); - auto layer = GetBaseLayer(m_Graph, output->index()); - auto sourceLayerIndex = layer->inputSlots()->Get(0)->connection()->sourceLayerIndex(); - auto sourceLayer = GetBaseLayer(m_Graph, sourceLayerIndex); - return std::make_pair(bindingId, ToTensorInfo(sourceLayer->outputSlots()->Get(0)->tensorInfo())); - } - } - throw ParseException( - boost::str( - boost::format("No output binding found for layer:%1% / %2%") % - name % - CHECK_LOCATION().AsString())); -} - -void DeserializeParser::SetupInputLayers() -{ - CHECK_GRAPH(m_Graph, 0); - auto inputs = GetGraphInputs(m_Graph); - for (auto const& input : inputs) - { - IConnectableLayer* layer = - m_Network->AddInputLayer(GetBindingLayerInfo(m_Graph, input->index()), input->layerName()->c_str()); - - auto tensorInfo = ToTensorInfo(input->outputSlots()->Get(0)->tensorInfo()); - layer->GetOutputSlot(0).SetTensorInfo(tensorInfo); - - RegisterOutputSlots(input->index(), layer); - } -} - -void DeserializeParser::SetupOutputLayers() -{ - CHECK_GRAPH(m_Graph, 0); - auto outputs = GetGraphOutputs(m_Graph); - for (auto const& output : outputs) - { - IConnectableLayer* layer = - m_Network->AddOutputLayer(GetBindingLayerInfo(m_Graph, output->index()), output->layerName()->c_str()); - - RegisterInputSlots(output->index(), layer); - } -} - -void DeserializeParser::RegisterOutputSlots(uint32_t layerIndex, - IConnectableLayer* layer) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - BOOST_ASSERT(layer != nullptr); - auto parsedLayer = GetBaseLayer(m_Graph, layerIndex); - if (parsedLayer->outputSlots()->size() != layer->GetNumOutputSlots()) - { - throw ParseException( - boost::str(boost::format("The number of outputslots (%1%) does not match the number expected (%2%)" - " for layer index: %3% %4%") % - parsedLayer->outputSlots()->size() % - layer->GetNumOutputSlots() % - layerIndex % - CHECK_LOCATION().AsString())); - } - - for (unsigned int slotIndex = 0; slotIndex < layer->GetNumOutputSlots(); ++slotIndex) - { - armnn::IOutputSlot* slot = &(layer->GetOutputSlot(slotIndex)); - RegisterOutputSlotOfConnection(layerIndex, slot); - } -} - -void DeserializeParser::RegisterInputSlots(uint32_t layerIndex, - armnn::IConnectableLayer* layer) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - BOOST_ASSERT(layer != nullptr); - auto parsedLayer = GetBaseLayer(m_Graph, layerIndex); - if (parsedLayer->inputSlots()->size() != layer->GetNumInputSlots()) - { - throw ParseException( - boost::str(boost::format("The number of inputslots (%1%) does not match the number expected (%2%)" - " for layer index:%3% %4%") % - parsedLayer->inputSlots()->size() % - layer->GetNumInputSlots() % - layerIndex % - CHECK_LOCATION().AsString())); - } - - for (unsigned int slotIndex = 0; slotIndex < layer->GetNumInputSlots(); ++slotIndex) - { - armnn::IInputSlot* slot = &(layer->GetInputSlot(slotIndex)); - uint32_t sourceLayerIndex = parsedLayer->inputSlots()->Get(slotIndex)->connection()->sourceLayerIndex(); - RegisterInputSlotOfConnection(sourceLayerIndex, slot); - } -} - -void DeserializeParser::RegisterInputSlotOfConnection(uint32_t connectionIndex, - armnn::IInputSlot* slot) -{ - BOOST_ASSERT(m_GraphConnections[0].size() > connectionIndex); - - Slots& slots = m_GraphConnections[0][connectionIndex]; - slots.inputSlots.push_back(slot); -} - -void DeserializeParser::RegisterOutputSlotOfConnection(uint32_t connectionIndex, - armnn::IOutputSlot* slot) -{ - BOOST_ASSERT(m_GraphConnections[0].size() > connectionIndex); - - Slots& slots = m_GraphConnections[0][connectionIndex]; - - // assuming there is only one producer for that tensor - if (slots.outputSlot != nullptr) - { - throw ParseException(boost::str( - boost::format("Another layer has already registered itself as the producer of " - "connection:%1% / %2%") % - connectionIndex % - CHECK_LOCATION().AsString())); - } - - slots.outputSlot = slot; -} - -void DeserializeParser::ParseAdd(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto inputs = GetInputs(m_Graph, layerIndex); - CHECK_LOCATION(); - CHECK_VALID_SIZE(inputs.size(), 2); - - auto outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - - m_layerName = boost::str(boost::format("Addition:%1%") % layerIndex); - IConnectableLayer* layer = m_Network->AddAdditionLayer(m_layerName.c_str()); - - armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); - layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -void DeserializeParser::ParseConvolution2d(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto inputs = GetInputs(m_Graph, layerIndex); - CHECK_LOCATION(); - CHECK_VALID_SIZE(inputs.size(), 1); - - auto outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - - auto layerName = boost::str(boost::format("Convolution2d:%1%") % layerIndex); - - auto serializerLayer = m_Graph->layers()->Get(layerIndex)->layer_as_Convolution2dLayer(); - auto serializerDescriptor = serializerLayer->descriptor(); - - armnn::Convolution2dDescriptor descriptor; - descriptor.m_PadLeft = serializerDescriptor->padLeft(); - descriptor.m_PadRight = serializerDescriptor->padRight(); - descriptor.m_PadTop = serializerDescriptor->padTop(); - descriptor.m_PadBottom = serializerDescriptor->padBottom(); - descriptor.m_StrideX = serializerDescriptor->strideX(); - descriptor.m_StrideY = serializerDescriptor->strideY();; - descriptor.m_BiasEnabled = serializerDescriptor->biasEnabled();; - descriptor.m_DataLayout = ToDataLayout(serializerDescriptor->dataLayout()); - - armnn::ConstTensor weights = ToConstTensor(serializerLayer->weights()); - armnn::ConstTensor biases; - - if (descriptor.m_BiasEnabled) - { - biases = ToConstTensor(serializerLayer->biases()); - } - IConnectableLayer* layer = m_Network->AddConvolution2dLayer(descriptor, - weights, - biases, - layerName.c_str()); - armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); - layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -void DeserializeParser::ParseDepthwiseConvolution2d(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto inputs = GetInputs(m_Graph, layerIndex); - CHECK_LOCATION(); - CHECK_VALID_SIZE(inputs.size(), 1); - - auto outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - - auto layerName = boost::str(boost::format("DepthwiseConvolution2d:%1%") % layerIndex); - - auto serializerLayer = m_Graph->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer(); - auto serializerDescriptor = serializerLayer->descriptor(); - - armnn::DepthwiseConvolution2dDescriptor descriptor; - descriptor.m_PadLeft = serializerDescriptor->padLeft(); - descriptor.m_PadRight = serializerDescriptor->padRight(); - descriptor.m_PadTop = serializerDescriptor->padTop(); - descriptor.m_PadBottom = serializerDescriptor->padBottom(); - descriptor.m_StrideX = serializerDescriptor->strideX(); - descriptor.m_StrideY = serializerDescriptor->strideY();; - descriptor.m_BiasEnabled = serializerDescriptor->biasEnabled();; - descriptor.m_DataLayout = ToDataLayout(serializerDescriptor->dataLayout()); - - armnn::ConstTensor weights = ToConstTensor(serializerLayer->weights()); - armnn::ConstTensor biases; - - if (descriptor.m_BiasEnabled) - { - biases = ToConstTensor(serializerLayer->biases()); - } - IConnectableLayer* layer = m_Network->AddDepthwiseConvolution2dLayer(descriptor, - weights, - biases, - layerName.c_str()); - - armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); - layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -void DeserializeParser::ParseMultiplication(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto inputs = GetInputs(m_Graph, layerIndex); - CHECK_LOCATION(); - CHECK_VALID_SIZE(inputs.size(), 2); - - auto outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - - m_layerName = boost::str(boost::format("Multiplication:%1%") % layerIndex); - IConnectableLayer* layer = m_Network->AddMultiplicationLayer(m_layerName.c_str()); - - armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); - layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -armnn::Pooling2dDescriptor DeserializeParser::GetPoolingDescriptor(DeserializeParser::PoolingDescriptor pooling2dDesc, - unsigned int layerIndex) -{ - armnn::Pooling2dDescriptor desc; - - switch (pooling2dDesc->poolType()) - { - case PoolingAlgorithm_Average: - { - desc.m_PoolType = armnn::PoolingAlgorithm::Average; - m_layerName = boost::str(boost::format("AveragePool2D:%1%") % layerIndex); - break; - } - case PoolingAlgorithm_Max: - { - desc.m_PoolType = armnn::PoolingAlgorithm::Max; - m_layerName = boost::str(boost::format("MaxPool2D:%1%") % layerIndex); - break; - } - default: - { - BOOST_ASSERT_MSG(false, "Unsupported pooling algorithm"); - } - } - - switch (pooling2dDesc->outputShapeRounding()) - { - case OutputShapeRounding_Floor: - { - desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor; - break; - } - case OutputShapeRounding_Ceiling: - { - desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Ceiling; - break; - } - default: - { - BOOST_ASSERT_MSG(false, "Unsupported output shape rounding"); - } - } - - switch (pooling2dDesc->paddingMethod()) - { - case PaddingMethod_Exclude: - { - desc.m_PaddingMethod = armnn::PaddingMethod::Exclude; - break; - } - case PaddingMethod_IgnoreValue: - { - desc.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue; - break; - } - default: - { - BOOST_ASSERT_MSG(false, "Unsupported padding method"); - } - } - - switch (pooling2dDesc->dataLayout()) - { - case DataLayout_NCHW: - { - desc.m_DataLayout = armnn::DataLayout::NCHW; - break; - } - case DataLayout_NHWC: - { - desc.m_DataLayout = armnn::DataLayout::NHWC; - break; - } - default: - { - BOOST_ASSERT_MSG(false, "Unsupported data layout"); - } - } - - desc.m_PadRight = pooling2dDesc->padRight(); - desc.m_PadLeft = pooling2dDesc->padLeft(); - desc.m_PadBottom = pooling2dDesc->padBottom(); - desc.m_PadTop = pooling2dDesc->padTop(); - desc.m_StrideX = pooling2dDesc->strideX(); - desc.m_StrideY = pooling2dDesc->strideY(); - desc.m_PoolWidth = pooling2dDesc->poolWidth(); - desc.m_PoolHeight = pooling2dDesc->poolHeight(); - - return desc; -} - -void DeserializeParser::ParsePooling2d(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - - auto pooling2dDes = m_Graph->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->descriptor(); - - auto inputs = GetInputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(inputs.size(), 1); - - auto outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - auto outputInfo = ToTensorInfo(outputs[0]); - - auto pooling2dDescriptor = GetPoolingDescriptor(pooling2dDes, layerIndex); - - IConnectableLayer* layer = m_Network->AddPooling2dLayer(pooling2dDescriptor, m_layerName.c_str()); - layer->GetOutputSlot(0).SetTensorInfo(outputInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -armnn::TensorInfo DeserializeParser::OutputShapeOfReshape(const armnn::TensorInfo& inputTensorInfo, - const std::vector<uint32_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()); - - armnn::TensorInfo reshapeInfo = inputTensorInfo; - reshapeInfo.SetShape(outputShape); - - return reshapeInfo; -} - -void DeserializeParser::ParseReshape(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - auto inputs = GetInputs(m_Graph, layerIndex); - - auto outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - - armnn::TensorInfo inputTensorInfo = ToTensorInfo(inputs[0]); - armnn::TensorInfo actualOutputTensorInfo = ToTensorInfo(outputs[0]); - - const auto targetDims = m_Graph->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->descriptor()->targetShape(); - std::vector<uint32_t> outputDims(targetDims->begin(), targetDims->begin() + targetDims->size()); - - armnn::TensorInfo reshapeOutputTensorInfo = DeserializeParser::OutputShapeOfReshape(inputTensorInfo, outputDims); - const armnn::TensorShape& reshapeOutputTensorShape = reshapeOutputTensorInfo.GetShape(); - - const std::vector<uint32_t> expectedDims(outputs[0]->dimensions()->begin(), - outputs[0]->dimensions()->begin() + outputs[0]->dimensions()->size()); - - if (inputs.size() > 1 && !CheckShape(reshapeOutputTensorShape, expectedDims)) - { - std::stringstream ss; - ss << "New shape defined in reshape parameters " - << reshapeOutputTensorShape - << " does not equal output shape " - << actualOutputTensorInfo.GetShape() - << ": " - << CHECK_LOCATION().AsString(); - throw ParseException(ss.str()); - } - - armnn::ReshapeDescriptor reshapeDesc; - reshapeDesc.m_TargetShape = reshapeOutputTensorShape; - - auto layerName = boost::str(boost::format("Reshape:%1%") % layerIndex); - IConnectableLayer* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str()); - layer->GetOutputSlot(0).SetTensorInfo(reshapeOutputTensorInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -void DeserializeParser::ParseSoftmax(unsigned int layerIndex) -{ - CHECK_LAYERS(m_Graph, 0, layerIndex); - - DeserializeParser::TensorRawPtrVector inputs = GetInputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(inputs.size(), 1); - - DeserializeParser::TensorRawPtrVector outputs = GetOutputs(m_Graph, layerIndex); - CHECK_VALID_SIZE(outputs.size(), 1); - - armnn::SoftmaxDescriptor descriptor; - descriptor.m_Beta = m_Graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->beta(); - - const std::string layerName = boost::str(boost::format("Softmax:%1%") % layerIndex); - IConnectableLayer* layer = m_Network->AddSoftmaxLayer(descriptor, layerName.c_str()); - - armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); - layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); - - RegisterInputSlots(layerIndex, layer); - RegisterOutputSlots(layerIndex, layer); -} - -} // namespace armnnDeserializeParser |