std::unique_ptr<feature_selector>
make_selector(const cpptoml::table& config,
std::shared_ptr<index::forward_index> idx)
{
auto table = config.get_table("features");
if (!table)
throw selector_factory_exception{
"[features] table missing from config file"};
auto prefix = table->get_as<std::string>("prefix");
if (!prefix)
throw selector_factory_exception{"no prefix in [features] table"};
auto method = table->get_as<std::string>("method");
if (!method)
throw selector_factory_exception{
"feature selection method required in [features] table"};
auto features_per_class = static_cast<uint64_t>(
table->get_as<int64_t>("features-per-class").value_or(20));
auto selector
= selector_factory::get().create(*method, *table, std::move(idx));
selector->init(features_per_class); // make_selector is a friend
return selector;
}
std::unique_ptr<classifier>
make_classifier<dual_perceptron>(const cpptoml::table& config,
multiclass_dataset_view training)
{
auto alpha = config.get_as<double>("alpha")
.value_or(dual_perceptron::default_alpha);
auto gamma = config.get_as<double>("gamma")
.value_or(dual_perceptron::default_gamma);
auto bias
= config.get_as<double>("bias").value_or(dual_perceptron::default_bias);
auto max_iter = config.get_as<int64_t>("max-iter")
.value_or(dual_perceptron::default_max_iter);
auto kernel_cfg = config.get_table("kernel");
if (!kernel_cfg)
return make_unique<dual_perceptron>(std::move(training),
make_unique<kernel::polynomial>(),
alpha, gamma, bias, max_iter);
return make_unique<dual_perceptron>(std::move(training),
kernel::make_kernel(*kernel_cfg), alpha,
gamma, bias, max_iter);
}
std::unique_ptr<classifier>
make_classifier<one_vs_all>(const cpptoml::table& config,
std::shared_ptr<index::forward_index> idx)
{
auto base = config.get_table("base");
if (!base)
throw classifier_factory::exception{
"one-vs-all missing base-classifier parameter in config file"};
return make_unique<one_vs_all>(idx, [&](class_label positive_label)
{
return make_binary_classifier(*base, idx, positive_label,
class_label{"negative"});
});
}
language_model::language_model(const cpptoml::table& config)
{
auto table = config.get_table("language-model");
auto arpa_file = table->get_as<std::string>("arpa-file");
auto binary_file = table->get_as<std::string>("binary-file-prefix");
N_ = 0;
if (binary_file && filesystem::file_exists(*binary_file + "0.binlm"))
{
LOG(info) << "Loading language model from binary files: "
<< *binary_file << "*" << ENDLG;
auto time = common::time(
[&]()
{
prefix_ = *binary_file;
load_vocab();
while (filesystem::file_exists(*binary_file + std::to_string(N_)
+ ".binlm"))
lm_.emplace_back(*binary_file + std::to_string(N_++)
+ ".binlm");
});
LOG(info) << "Done. (" << time.count() << "ms)" << ENDLG;
}
else if (arpa_file && binary_file)
{
LOG(info) << "Loading language model from .arpa file: " << *arpa_file
<< ENDLG;
prefix_ = *binary_file;
auto time = common::time([&]()
{
read_arpa_format(*arpa_file);
});
LOG(info) << "Done. (" << time.count() << "ms)" << ENDLG;
}
else
throw language_model_exception{
"arpa-file or binary-file-prefix needed in config file"};
// cache this value
auto unk = vocabulary_.at("<unk>");
unk_node_ = *lm_[0].find(&unk, &unk + 1);
}
/**
* Parses all sentences in a text file.
*/
void parse(const std::string& file, const cpptoml::table& config)
{
std::cout << "Running parser" << std::endl;
auto seq_grp = config.get_table("sequence");
if (!seq_grp)
{
std::cerr << "[sequence] group needed in config file" << std::endl;
return;
}
auto prefix = seq_grp->get_as<std::string>("prefix");
if (!prefix)
{
std::cerr << "[sequence] group needs a prefix key" << std::endl;
return;
}
auto parser_grp = config.get_table("parser");
if (!parser_grp)
{
std::cerr << "[parser] group needed in config file" << std::endl;
return;
}
auto parser_prefix = parser_grp->get_as<std::string>("prefix");
if (!parser_prefix)
{
std::cerr << "[parser] group needs a prefix key" << std::endl;
return;
}
std::cout << "Loading tagging model" << std::endl;
// load POS-tagging model
sequence::perceptron tagger{*prefix};
std::cout << "Loading parser model" << std::endl;
// load parser model
parser::sr_parser parser{*parser_prefix};
// construct the token filter chain
std::unique_ptr<analyzers::token_stream> stream
= make_unique<analyzers::tokenizers::icu_tokenizer>();
stream = make_unique<analyzers::filters::ptb_normalizer>(std::move(stream));
stream->set_content(filesystem::file_text(file));
// parse each sentence in the file
// and write its output to the output file
auto out_name = no_ext(file) + ".parsed.txt";
std::ofstream outfile{out_name};
sequence::sequence seq;
while (*stream)
{
auto token = stream->next();
if (token == "<s>")
{
seq = {};
}
else if (token == "</s>")
{
tagger.tag(seq);
parser.parse(seq).pretty_print(outfile);
}
else
{
seq.add_symbol(sequence::symbol_t{token});
}
}
std::cout << " -> file saved as " << out_name << std::endl;
}
/**
* Performs part-of-speech tagging on a text file.
* @param file The input file
* @param config Configuration settings
* @param replace Whether or not to replace words with their POS tags
*/
void pos(const std::string& file, const cpptoml::table& config, bool replace)
{
std::cout << "Running POS-tagging with replace = " << std::boolalpha
<< replace << std::endl;
auto seq_grp = config.get_table("sequence");
if (!seq_grp)
{
std::cerr << "[sequence] group needed in config file" << std::endl;
return;
}
auto prefix = seq_grp->get_as<std::string>("prefix");
if (!prefix)
{
std::cerr << "[sequence] group needs a prefix key" << std::endl;
return;
}
std::cout << "Loading tagging model" << std::endl;
sequence::perceptron tagger{*prefix};
// construct the token filter chain
std::unique_ptr<analyzers::token_stream> stream
= make_unique<analyzers::tokenizers::icu_tokenizer>();
stream = make_unique<analyzers::filters::ptb_normalizer>(std::move(stream));
stream->set_content(filesystem::file_text(file));
// tag each sentence in the file
// and write its output to the output file
auto out_name = no_ext(file)
+ (replace ? ".pos-replace.txt" : ".pos-tagged.txt");
std::ofstream outfile{out_name};
sequence::sequence seq;
while (*stream)
{
auto token = stream->next();
if (token == "<s>")
{
seq = {};
}
else if (token == "</s>")
{
tagger.tag(seq);
for (const auto& obs : seq)
{
if (replace)
outfile << obs.tag() << " ";
else
outfile << obs.symbol() << "_" << obs.tag() << " ";
}
outfile << std::endl;
}
else
{
seq.add_symbol(sequence::symbol_t{token});
}
}
std::cout << " -> file saved as " << out_name << std::endl;
}