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Diffstat (limited to 'src/armnnCaffeParser/RecordByRecordCaffeParser.cpp')
| -rw-r--r-- | src/armnnCaffeParser/RecordByRecordCaffeParser.cpp | 731 |
1 files changed, 0 insertions, 731 deletions
diff --git a/src/armnnCaffeParser/RecordByRecordCaffeParser.cpp b/src/armnnCaffeParser/RecordByRecordCaffeParser.cpp deleted file mode 100644 index b7ff3d8731..0000000000 --- a/src/armnnCaffeParser/RecordByRecordCaffeParser.cpp +++ /dev/null @@ -1,731 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "RecordByRecordCaffeParser.hpp" - -#include "armnn/Exceptions.hpp" -#include "armnn/Utils.hpp" -#include <armnn/utility/NumericCast.hpp> - -#include "GraphTopologicalSort.hpp" - -// Caffe -#include <google/protobuf/wire_format.h> - - -//#include <stdio.h> -#include <limits.h> -#include <sstream> -//#include <iostream> -#include <fstream> - -namespace armnnCaffeParser -{ -// class which holds information on the absolute position in the stream -// of the data and the length of the data record. -class VarLenDataInfo -{ -public: - VarLenDataInfo(std::streamoff positionOfData, size_t sizeOfData) : - m_PositionOfData(positionOfData), m_SizeOfData(sizeOfData) {} - - VarLenDataInfo(const VarLenDataInfo& x) : - m_PositionOfData(x.PositionOfData()), m_SizeOfData (x.SizeOfData()) {} - - VarLenDataInfo& operator=(const VarLenDataInfo& x) - { - // handle self assignment - if (this == &x) { - return *this; - } - m_PositionOfData = x.PositionOfData(); m_SizeOfData = x.SizeOfData(); return *this; - } - - std::streamoff PositionOfData() const {return m_PositionOfData;} - size_t SizeOfData() const {return m_SizeOfData;} - -private: - std::streamoff m_PositionOfData; - size_t m_SizeOfData; - -}; - -// class which holds enough information on a LayerParameter in the Caffe protobuf -// format to allow it to be resolved for in place layering and sorted topologically -// prior to the entire record being parsed into memory. -// -// NOTE: function naming follows that of the protobuf classes these proxies are standing in for -class LayerParameterInfo : public VarLenDataInfo -{ -public: - static const std::string INPUT; - LayerParameterInfo(const VarLenDataInfo& varLenDataInfo) : - VarLenDataInfo(varLenDataInfo.PositionOfData(), varLenDataInfo.SizeOfData()), - m_newTops(false), m_newBottoms(false) {} - - LayerParameterInfo(std::streamoff positionOfData, size_t sizeOfData) : - VarLenDataInfo(positionOfData, sizeOfData), m_newTops(false), m_newBottoms(false) {} - - LayerParameterInfo(const LayerParameterInfo& x) : - VarLenDataInfo(x.PositionOfData(), x.SizeOfData()), - m_name(x.m_name), - m_type(x.m_type), - m_tops(x.m_tops), - m_bottoms(x.m_bottoms), - m_newTops(x.m_newTops), - m_newBottoms(x.m_newBottoms) {} - - LayerParameterInfo& operator=(const LayerParameterInfo& x) - { - if (this == &x) { - return *this; - } - VarLenDataInfo::operator=(x); - m_name = x.m_name; - m_type = x.m_type; - m_tops = x.m_tops; - m_bottoms = x.m_bottoms; - m_newTops = x.m_newTops; - m_newBottoms = x.m_newBottoms; - return *this; - } - - const std::string name() const {return m_name;} - void set_name(const std::unique_ptr<char[]>& theName, size_t length) - { - m_name = std::string(theName.get(), length); - } - void set_name(const std::string& theName) {m_name = theName;} - - const std::string type() const {return m_type;} - void set_type(const std::unique_ptr<char[]>& theType, size_t length) - { - m_type = std::string(theType.get(), length); - } - void set_type(const std::string& theType) {m_type = theType;} - - void add_top(const std::unique_ptr<char[]>& top, size_t length) - { - std::string topName(top.get(), length); - m_tops.push_back(topName); - } - void add_top(const std::string& topName) - { - m_tops.push_back(topName); - } - const std::string top(unsigned long i) const {return m_tops[i];} - unsigned long top_size() const {return m_tops.size();} - void set_top(unsigned long i, const std::string& newName) {m_tops[i] = newName; m_newTops = true;} - bool new_tops() const {return m_newTops;} - - void add_bottom(const std::unique_ptr<char[]>& bottom, size_t length) - { - std::string bottomName(bottom.get(), length); - m_bottoms.push_back(bottomName); - } - unsigned long bottom_size() const {return m_bottoms.size();} - const std::string bottom(unsigned long i) const {return m_bottoms[i];} - void set_bottom(unsigned long i, const std::string& newName) {m_bottoms[i] = newName; m_newBottoms = true;} - bool new_bottoms() const {return m_newBottoms;} - - // if the position and size of the data is zero and the type is "Input" then this is an 'Implicit Input Layer' - // and needs to be handled differently from ordinary layers. - bool isImplicitInputLayer() const - { - if ((PositionOfData() == 0) && (SizeOfData() == 0) && INPUT.compare(type()) == 0) - {return true;} else {return false;} - } - -private: - std::string m_name; - std::string m_type; - std::vector<std::string> m_tops; - std::vector<std::string> m_bottoms; - // mark the layers whose topology was changed - // by the ResolveInPlaceLayers method. - bool m_newTops; - bool m_newBottoms; -}; - -// class which holds the field type (wire type) and field id (id from the .proto schema) -// read from the protobuf messages as per the binary encoding described in -// https://developers.google.com/protocol-buffers/docs/encoding -// -// NOTE: function naming follows that of the protobuf classes these proxies are standing in for -class ProtobufFieldInfo -{ -public: - ProtobufFieldInfo(int field_type, int field_id) : - m_eof(false), m_field_type(field_type), m_field_id(field_id) {} - ProtobufFieldInfo() : m_eof(true), m_field_type(0), m_field_id(0) {} - - bool eof() {return m_eof;} - int field_type() {return m_field_type;} - int field_id() {return m_field_id;} - -private: - bool m_eof; - int m_field_type; - int m_field_id; -}; - - -// There are some NetParameter level data which are required -// to correctly processes some Caffe models. Specifically those which -// have 'implicit' input layers. Also it is nice to have the name of the model. -// -// NOTE: function naming follows that of the protobuf classes these proxies are standing in for -class NetParameterInfo -{ -public: - const std::string name() const {return m_name;} - void set_name(const std::unique_ptr<char[]>& theName, size_t length) - { - m_name = std::string(theName.get(), length); - } - - void add_input(const std::unique_ptr<char[]>& input, size_t length) - { - std::string inputName(input.get(), length); - m_inputs.push_back(inputName); - } - const std::string input(unsigned long i) const {return m_inputs[i];} - unsigned long input_size() const {return m_inputs.size();} - - void add_input_dimension(int input_dimension) { - m_input_dimensions.push_back(input_dimension); - } - int input_dimension(unsigned long i) const {return m_input_dimensions[i];} - unsigned long input_dimensions_size() const {return m_input_dimensions.size();} - - void add_blob_shape(caffe::BlobShape shape) { - m_blob_shapes.push_back(shape); - } - const caffe::BlobShape blob_shape(unsigned long i) const {return m_blob_shapes[i];} - unsigned long blob_shapes_size() const {return m_blob_shapes.size();} - -private: - std::string m_name; - std::vector<std::string> m_inputs; - std::vector<int> m_input_dimensions; - std::vector<caffe::BlobShape> m_blob_shapes; - -}; - -}; // namespace armnnCaffeParser - -using namespace armnnCaffeParser; - -// Initialise the class const -const std::string LayerParameterInfo::INPUT = "Input"; - -namespace -{ - -ProtobufFieldInfo readFieldInfo(std::ifstream& ifs) -{ - unsigned char first_byte = static_cast<unsigned char>(ifs.get()); - if (!ifs.good()) - { - ProtobufFieldInfo eof; - return eof; - } - int field_type = first_byte&7; - int field_id = first_byte>>3; - if ((field_id & 16) == 16) - { - unsigned char second_byte = static_cast<unsigned char>(ifs.get()); - if (!ifs.good()) - { - ProtobufFieldInfo eof; - return eof; - } - field_id = (field_id-16) + ((second_byte&127)<<4); - } - ProtobufFieldInfo fieldInfo(field_type, field_id); - return fieldInfo; -} - -const static int MAX_NUM_BYTES = 5; - -int ReadBase128(std::ifstream& ifs) -{ - int result = 0; - unsigned int shift_by = 0; - int bytesRead = 0; - while (true) - { - unsigned char a_byte = static_cast<unsigned char>(ifs.get()); - ++bytesRead; - if (bytesRead > MAX_NUM_BYTES) - { - throw armnn::ParseException( - "ReadBase128 exceeded the maximum number of bytes expected for an integer representation"); - } - result += (a_byte & 127) << shift_by; - shift_by += 7; - if ((a_byte & 128) != 128) - { - break; - } - } - return result; -} - - -std::unique_ptr<char[]> AllocateBuffer(std::ifstream& ifs, VarLenDataInfo& dataInfo) -{ - std::unique_ptr<char[]> ptr(new char[dataInfo.SizeOfData()]); - ifs.clear(); - ifs.seekg(dataInfo.PositionOfData(), std::ios_base::beg); - ifs.read(ptr.get(), armnn::numeric_cast<std::streamsize>(dataInfo.SizeOfData())); - return ptr; -} - -VarLenDataInfo CreateVarLenDataInfo(std::streamoff bufferStart, std::streamoff endOfLayer) { - std::streamoff sizeOfLayer = endOfLayer - bufferStart; - if (sizeOfLayer < 0) - { - std::stringstream ss; - ss << "error when determining buffer size, negative value [" << sizeOfLayer << "]"; - throw armnn::ParseException(ss.str()); - } - // NOTE: as some of the data being read in will be translated into strings (names of layers etc) - // the maximum size we can deal with is the upper size limit of a string i.e. size_t - // on the platform in which I am currently compiling std::streamoff is signed long int and - // size_t is unsigned long int so there is no way this error condition can fire but this stuff - // is supposed to be portable so the check remains in place - if (armnn::numeric_cast<size_t>(sizeOfLayer) > SIZE_MAX) { - std::stringstream ss; - ss << "layer is greater than " << SIZE_MAX << " in size cannot process. layer size = [" << sizeOfLayer << "]"; - throw armnn::ParseException(ss.str()); - } - LayerParameterInfo info(bufferStart, armnn::numeric_cast<size_t>(sizeOfLayer)); - return info; -} - -void ReadTopologicalInfoForLayerParameter(LayerParameterInfo& layerInfo, std::ifstream& ifs) -{ - // position the file pointer to the start of the layer data - ifs.clear(); - ifs.seekg(layerInfo.PositionOfData(), std::ios_base::beg); - std::streamoff endOfLayer = layerInfo.PositionOfData() + - armnn::numeric_cast<std::streamoff>(layerInfo.SizeOfData()); - while(true) - { - // check to see if we have reached the end of the record - std::streamoff currentPosition = ifs.tellg(); - if (currentPosition >= endOfLayer) { - return; - } - // read the information for the next field. - ProtobufFieldInfo fieldInfo = readFieldInfo(ifs); - if (fieldInfo.eof()) - { - return; - // TODO: figure out whether this is an error condition or not... - //throw armnn::ParseException("failed to read field from LayerParameter data"); - } - // process the field - switch (fieldInfo.field_type()) - { - case 0: - { - ReadBase128(ifs); - break; - } - case 2: - { - int size = ReadBase128(ifs); - std::streamoff posStartOfData = ifs.tellg(); - VarLenDataInfo dataInfo(posStartOfData, armnn::numeric_cast<size_t>(size)); - //optional string name = 1; // the layer name - //optional string type = 2; // the layer type - //repeated string bottom = 3; // the name of each bottom blob - //repeated string top = 4; // the name of each top blob - if (fieldInfo.field_id() == 1) - { - // read and set the name of the layer - auto layerName = AllocateBuffer(ifs, dataInfo); - layerInfo.set_name(layerName, dataInfo.SizeOfData()); - } - else if (fieldInfo.field_id() == 2) - { - // read and set the type of the layer - auto layerType = AllocateBuffer(ifs, dataInfo); - layerInfo.set_type(layerType, dataInfo.SizeOfData()); - } - else if (fieldInfo.field_id() == 3) - { - // read and add a bottom to the layer - auto bottom = AllocateBuffer(ifs, dataInfo); - layerInfo.add_bottom(bottom, dataInfo.SizeOfData()); - } - else if (fieldInfo.field_id() == 4) - { - // read and add a top to the layer - auto top = AllocateBuffer(ifs, dataInfo); - layerInfo.add_top(top, dataInfo.SizeOfData()); - } - else - { - ifs.seekg(size, std::ios_base::cur); - if (!ifs.good()) - { - // TODO: error out? - return; - } - } - break; - } - case 1: - { - // 64 bit - // advance by eight bytes - ifs.seekg(8, std::ios_base::cur); - if (!ifs.good()) - { - // TODO: error out? - return; - } - break; - } - case 5: - { - // 32 bit - // advance by four bytes - ifs.seekg(4, std::ios_base::cur); - if (!ifs.good()) - { - // TODO: error out? - return; - } - break; - } - default: - { - throw armnn::ParseException("Encounted an unknown field type"); - break; - } - } - } -} - -void ResolveInPlaceLayers(std::vector<LayerParameterInfo>& layerInfo) -{ - std::map<std::string, std::vector<LayerParameterInfo*>> layersByTop; - for (auto& info : layerInfo) - { - for (unsigned long i = 0; i < info.top_size(); ++i) - { - layersByTop[info.top(i)].push_back(&info); - } - } - // For each set of layers with the same top, resolve them to a linear chain rather than in-place layers. - // Note that for 'regular' layers, there will be a single layer in each group and so this will be a no-op. - for (auto& layersWithSameTopIterator : layersByTop) - { - const std::string& top = layersWithSameTopIterator.first; - const std::vector<LayerParameterInfo*> layersWithSameTop = layersWithSameTopIterator.second; - - // Chain the layers together in the order that they are listed in the prototxt (hopefully this is correct). - // Note that the last layer will not have its top modified so that other layers will continue to reference it. - for (unsigned int layerIdx = 0; layerIdx < layersWithSameTop.size() - 1; ++layerIdx) - { - LayerParameterInfo* layer1 = layersWithSameTop[layerIdx]; - LayerParameterInfo* layer2 = layersWithSameTop[layerIdx + 1]; - if (layer1->top_size() != 1) - { - throw armnn::ParseException("Node '" + layer1->name() + "' is an in-place layer but " - "doesn't have exactly one top."); - } - std::string newTop = layer1->name() + "_top"; - layer1->set_top(0, newTop); - if (layer2->bottom_size() != 1 || layer2->bottom(0) != top) - { - throw armnn::ParseException("Node '" + layer2->name() + "' is an in-place layer but " - " doesn't have exactly one bottom, or it doesn't match its top."); - } - layer2->set_bottom(0, newTop); - - } - } -} - -} // anonymous namespace, can't be seen outside this source file - -RecordByRecordCaffeParser::RecordByRecordCaffeParser() : CaffeParserImpl() -{} - -armnn::INetworkPtr RecordByRecordCaffeParser::CreateNetworkFromBinaryFile( - const char* graphFile, - const std::map<std::string, armnn::TensorShape>& inputShapes, - const std::vector<std::string>& requestedOutputs) -{ - - m_InputShapes = inputShapes; - if (requestedOutputs.size() == 0) - { - throw armnn::ParseException("requestedOutputs must have at least one entry"); - } - m_RequestedOutputs = requestedOutputs; - - std::ifstream ifs(graphFile, std::ifstream::in|std::ifstream::binary); - if (ifs.fail()) - { - throw armnn::FileNotFoundException("Failed to open graph file '" + std::string(graphFile) + "'"); - } - - std::vector<LayerParameterInfo> layerInfo; - NetParameterInfo netParameterInfo; - while(true) - { - ProtobufFieldInfo fieldInfo = readFieldInfo(ifs); - if (fieldInfo.eof()) - { - break; - } - switch(fieldInfo.field_type()) - { - case 0: - { - ReadBase128(ifs); - break; - } - case 2: - { - // The values of interest from the caffe.proto schema are: - // optional string name = 1; // consider giving the network a name - // DEPRECATED. See InputParameter. The input blobs to the network. - // repeated string input = 3; - // DEPRECATED. See InputParameter. The shape of the input blobs. - // repeated BlobShape input_shape = 8; - - // 4D input dimensions -- deprecated. Use "input_shape" instead. - // If specified, for each input blob there should be four - // values specifying the num, channels, height and width of the input blob. - // Thus, there should be a total of (4 * #input) numbers. - // repeated int32 input_dim = 4; - - // The layers that make up the net. Each of their configurations, including - // connectivity and behavior, is specified as a LayerParameter. - // repeated LayerParameter layer = 100; // ID 100 so layers are printed last. - - // The first four will (if present) be read into the NetParameterInfo - // the LayerParameters will be read into the LayerParameterInfo vector. - - int size = ReadBase128(ifs); - std::streamoff posStartOfData = ifs.tellg(); - ifs.seekg(size, std::ios_base::cur); - if(!ifs.good()) - { - throw armnn::ParseException("failed to seek ahead in binary caffe file"); - } - std::streamoff endOfLayer = ifs.tellg(); - if (fieldInfo.field_id() == 1) - { - VarLenDataInfo dataInfo = CreateVarLenDataInfo(posStartOfData, endOfLayer); - auto graphName = AllocateBuffer(ifs, dataInfo); - netParameterInfo.set_name(graphName, dataInfo.SizeOfData()); - } - if (fieldInfo.field_id() == 3) - { - VarLenDataInfo dataInfo = CreateVarLenDataInfo(posStartOfData, endOfLayer); - auto inputName = AllocateBuffer(ifs, dataInfo); - netParameterInfo.add_input(inputName, dataInfo.SizeOfData()); - } - if (fieldInfo.field_id() == 8) - { - VarLenDataInfo dataInfo = CreateVarLenDataInfo(posStartOfData, endOfLayer); - auto inputShape = AllocateBuffer(ifs, dataInfo); - caffe::BlobShape blobShape; - bool bRet = blobShape.ParseFromArray(inputShape.get(), static_cast<int>(dataInfo.SizeOfData())); - if (!bRet) - { - throw armnn::ParseException("Failed to parse input shape"); - } - netParameterInfo.add_blob_shape(blobShape); - } - if (fieldInfo.field_id() == 4) - { - int input_dim = ReadBase128(ifs); - netParameterInfo.add_input_dimension(input_dim); - } - if (fieldInfo.field_id() == 100) - { - LayerParameterInfo info(CreateVarLenDataInfo(posStartOfData, endOfLayer)); - ReadTopologicalInfoForLayerParameter(info, ifs); - layerInfo.push_back(info); - } - break; - } - default: - { - break; - } - } - } - std::vector<const LayerParameterInfo*> sortedNodes; - ProcessLayers(netParameterInfo, layerInfo, m_RequestedOutputs, sortedNodes); - armnn::INetworkPtr networkPtr = LoadLayers(ifs, sortedNodes, netParameterInfo); - return networkPtr; - -} - -void RecordByRecordCaffeParser::ProcessLayers( - const NetParameterInfo& netParameterInfo, - std::vector<LayerParameterInfo>& layerInfo, - const std::vector<std::string>& m_RequestedOutputs, - std::vector<const LayerParameterInfo*>& sortedNodes) -{ - // if there is an implicit input layer add it to the layerInfo list - if (netParameterInfo.input_size() > 0) - { - LayerParameterInfo implicitInputLayer(0, 0); - implicitInputLayer.set_type(LayerParameterInfo::INPUT); - implicitInputLayer.set_name(netParameterInfo.input(0)); - implicitInputLayer.add_top(netParameterInfo.input(0)); - layerInfo.push_back(implicitInputLayer); - } - ::ResolveInPlaceLayers(layerInfo); - - for (LayerParameterInfo& info : layerInfo) - { - for (unsigned long i = 0; i < info.top_size(); ++i) - { - m_CaffeLayersByTopName[info.top(i)] = &info; - } - } - - // Find the output layers the user requested - std::vector<const LayerParameterInfo*> targetLayers; - for (const std::string& requestedOutputName : m_RequestedOutputs) - { - auto nodeIt = m_CaffeLayersByTopName.find(requestedOutputName); - if (nodeIt == m_CaffeLayersByTopName.end()) - { - throw armnn::ParseException( - "Couldn't find requested output layer '" + requestedOutputName + "' in graph"); - } - targetLayers.push_back(nodeIt->second); - } - - // Sort them into a linear ordering such that all inputs of a node are before the node itself - if (!armnnUtils::GraphTopologicalSort<const LayerParameterInfo*>( - targetLayers, - [this](const LayerParameterInfo* node) - { - return GetInputs(*node); - }, - sortedNodes)) - { - throw armnn::ParseException("Cycle detected in graph"); - } -} - - -std::vector<const LayerParameterInfo*> RecordByRecordCaffeParser::GetInputs( - const LayerParameterInfo& layerParam) -{ - std::vector<const LayerParameterInfo*> ret; - ret.reserve(layerParam.bottom_size()); - for (unsigned long j = 0; j < layerParam.bottom_size(); ++j) - { - std::string inputName = layerParam.bottom(j); - auto inputIt = m_CaffeLayersByTopName.find(inputName); - if (inputIt == m_CaffeLayersByTopName.end()) - { - throw armnn::ParseException( - "Can't find Caffe layer with top called '" + inputName + "', which is listed as an input of '" + - layerParam.name() + "'"); - } - ret.push_back(inputIt->second); - } - - return ret; -} - -armnn::INetworkPtr RecordByRecordCaffeParser::LoadLayers(std::ifstream& ifs, - std::vector<const LayerParameterInfo *>& sortedNodes, - const NetParameterInfo& netParameterInfo) -{ - - m_NetworkInputsBindingInfo.clear(); - m_NetworkOutputsBindingInfo.clear(); - - m_Network = armnn::INetwork::Create(); - - for (auto info : sortedNodes) - { - caffe::LayerParameter layer; - if (info->isImplicitInputLayer()) - { - // create the matching Layer Parameter programatically from the data in the - // net parameter info which has been passed in... - layer.set_type(LayerParameterInfo::INPUT); - layer.set_name(netParameterInfo.input(0)); - layer.add_top(netParameterInfo.input(0)); - - caffe::InputParameter* inputParam = layer.mutable_input_param(); - caffe::BlobShape* shape = inputParam->add_shape(); - - long unsigned int dim_size = netParameterInfo.input_dimensions_size(); - for (long unsigned int i = 0; i < dim_size; ++i) - { - shape->add_dim(netParameterInfo.input_dimension(i)); - } - } - else - { - char *buffer = new char[info->SizeOfData()]; - ifs.clear(); - ifs.seekg(info->PositionOfData(), std::ios_base::beg); - ifs.read(buffer, armnn::numeric_cast<std::streamsize>(info->SizeOfData())); - bool bRet = layer.ParseFromArray(buffer, static_cast<int>(info->SizeOfData())); - delete[] buffer; - if (!bRet) - { - throw armnn::ParseException("Failed to parse layer [" + info->name() + "]"); - } - } - - if (info->new_tops()) - { - //update the tops - layer.set_top(0, info->top(0)); - } - if (info->new_bottoms()) - { - //update the bottoms - layer.set_bottom(0, info->bottom(0)); - } - - auto it = ms_CaffeLayerNameToParsingFunctions.find(layer.type()); - if (it == ms_CaffeLayerNameToParsingFunctions.end()) - { - throw armnn::ParseException("Unsupported layer type '" + layer.type() + "'"); - } - auto func = it->second; - (this->*func)(layer); - } - ifs.close(); - - // Add ArmNN output layers connected to each requested output - for (const std::string& requestedOutput : m_RequestedOutputs) - { - armnn::IOutputSlot& outputSlot = GetArmnnOutputSlotForCaffeTop(requestedOutput); - - const armnn::LayerBindingId outputId = armnn::numeric_cast<armnn::LayerBindingId>( - m_NetworkOutputsBindingInfo.size()); - armnn::IConnectableLayer* const outputLayer = m_Network->AddOutputLayer(outputId, requestedOutput.c_str()); - outputSlot.Connect(outputLayer->GetInputSlot(0)); - - TrackOutputBinding(outputLayer, outputId, outputLayer->GetInputSlot(0).GetConnection()->GetTensorInfo()); - } - - Cleanup(); - - return move(m_Network); -} |