#include "ContextModule.hpp" ContextModuleImpl::ContextModuleImpl(std::string name, const std::string & definition, std::filesystem::path path) : path(path) { setName(name); std::regex regex("(?:(?:\\s|\\t)*)Targets\\{(.*)\\}(?:(?:\\s|\\t)*)Columns\\{(.*)\\}(?:(?:\\s|\\t)*)(\\S+)\\{(.*)\\}(?:(?:\\s|\\t)*)In\\{(.*)\\}(?:(?:\\s|\\t)*)Out\\{(.*)\\}(?:(?:\\s|\\t)*)w2v\\{(.*)\\}(?:(?:\\s|\\t)*)"); if (!util::doIfNameMatch(regex, definition, [this,&definition](auto sm) { try { for (auto & target : util::split(sm.str(1), ' ')) { auto splited = util::split(target, '.'); if (splited.size() != 2 and splited.size() != 3) util::myThrow(fmt::format("invalid target '{}' expected 'object.index(.childIndex)'", target)); targets.emplace_back(std::make_tuple(Config::str2object(splited[0]), std::stoi(splited[1]), splited.size() == 3 ? std::optional<int>(std::stoi(splited[2])) : std::optional<int>())); } auto funcColumns = util::split(sm.str(2), ' '); columns.clear(); for (auto & funcCol : funcColumns) { functions.emplace_back() = getFunction(funcCol); columns.emplace_back(util::split(funcCol, ':').back()); } auto subModuleType = sm.str(3); auto subModuleArguments = util::split(sm.str(4), ' '); auto options = MyModule::ModuleOptions(true) .bidirectional(std::stoi(subModuleArguments[0])) .num_layers(std::stoi(subModuleArguments[1])) .dropout(std::stof(subModuleArguments[2])) .complete(std::stoi(subModuleArguments[3])); inSize = std::stoi(sm.str(5)); int outSize = std::stoi(sm.str(6)); if (subModuleType == "LSTM") myModule = register_module("myModule", LSTM(columns.size()*inSize, outSize, options)); else if (subModuleType == "GRU") myModule = register_module("myModule", GRU(columns.size()*inSize, outSize, options)); else if (subModuleType == "Concat") myModule = register_module("myModule", Concat(inSize)); else if (subModuleType == "Transformer") myModule = register_module("myModule", Transformer(columns.size()*inSize, outSize, options)); else util::myThrow(fmt::format("unknown sumodule type '{}'", subModuleType)); w2vFiles = sm.str(7); if (!w2vFiles.empty()) { auto pathes = util::split(w2vFiles.string(), ' '); for (auto & p : pathes) { auto splited = util::split(p, ','); if (splited.size() != 2) util::myThrow("expected 'prefix,pretrained.w2v'"); auto pretrained = getDict().loadWord2Vec(this->path / splited[1], splited[0]); if (pretrained) { getDict().setState(Dict::State::Closed); dictSetPretrained(true); } } } } catch (std::exception & e) {util::myThrow(fmt::format("{} in '{}'",e.what(),definition));} })) util::myThrow(fmt::format("invalid definition '{}'", definition)); } std::size_t ContextModuleImpl::getOutputSize() { return myModule->getOutputSize(targets.size()); } std::size_t ContextModuleImpl::getInputSize() { return columns.size()*(targets.size()); } void ContextModuleImpl::addToContext(std::vector<std::vector<long>> & context, const Config & config) { auto & dict = getDict(); std::vector<long> contextIndexes; for (auto & target : targets) if (config.hasRelativeWordIndex(std::get<0>(target), std::get<1>(target))) { int baseIndex = config.getRelativeWordIndex(std::get<0>(target), std::get<1>(target)); if (!std::get<2>(target)) contextIndexes.emplace_back(baseIndex); else { int childIndex = *std::get<2>(target); auto childs = util::split(config.getAsFeature(Config::childsColName, baseIndex).get(), '|'); int candidate = -2; if (childIndex >= 0 and childIndex < (int)childs.size()) { candidate = std::stoi(childs[childIndex]); if (candidate > baseIndex) candidate = -2; } else if (childIndex < 0 and ((int)childs.size())+childIndex >= 0) { candidate = std::stoi(childs[childs.size()+childIndex]); if (candidate < baseIndex) candidate = -2; } contextIndexes.emplace_back(candidate); } } else contextIndexes.emplace_back(-1); for (auto index : contextIndexes) for (unsigned int colIndex = 0; colIndex < columns.size(); colIndex++) { auto & col = columns[colIndex]; if (index == -1) { for (auto & contextElement : context) contextElement.push_back(dict.getIndexOrInsert(Dict::nullValueStr, col)); } else if (index == -2) { for (auto & contextElement : context) contextElement.push_back(dict.getIndexOrInsert(Dict::noChildValueStr, col)); } else { int dictIndex; if (col == Config::idColName) { std::string value; if (config.isMultiwordPredicted(index)) value = "multiword"; else if (config.isTokenPredicted(index)) value = "token"; dictIndex = dict.getIndexOrInsert(value, col); } else { std::string featureValue = functions[colIndex](config.getAsFeature(col, index)); dictIndex = dict.getIndexOrInsert(featureValue, col); } for (auto & contextElement : context) contextElement.push_back(dictIndex); } } } torch::Tensor ContextModuleImpl::forward(torch::Tensor input) { auto context = wordEmbeddings(input.narrow(1, firstInputIndex, getInputSize())); context = context.view({context.size(0), context.size(1)/(int)columns.size(), (int)columns.size()*context.size(2)}); return myModule->forward(context).reshape({input.size(0), -1}); } void ContextModuleImpl::registerEmbeddings() { if (!wordEmbeddings) wordEmbeddings = register_module("embeddings", WordEmbeddings(getDict().size(), inSize)); auto pathes = util::split(w2vFiles.string(), ' '); for (auto & p : pathes) { auto splited = util::split(p, ','); loadPretrainedW2vEmbeddings(wordEmbeddings->get(), path / splited[1], splited[0]); } }