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#include "lm/model.hh"
#include "util/file_piece.hh"
#include <cstdlib>
#include <exception>
#include <iostream>
#include <iomanip>
#include <math.h>
#include <stdlib.h>
#ifdef WIN32
#include "util/getopt.hh"
#endif
namespace lm {
namespace ngram {
namespace {
void Usage(const char *name) {
std::cerr << "Usage: " << name << " [-u log10_unknown_probability] [-s] [-i] [-w mmap|after] [-p probing_multiplier] [-t trie_temporary] [-m trie_building_megabytes] [-q bits] [-b bits] [-a bits] [type] input.arpa [output.mmap]\n\n"
"-u sets the log10 probability for <unk> if the ARPA file does not have one.\n"
" Default is -100. The ARPA file will always take precedence.\n"
"-s allows models to be built even if they do not have <s> and </s>.\n"
"-i allows buggy models from IRSTLM by mapping positive log probability to 0.\n"
"-w mmap|after determines how writing is done.\n"
" mmap maps the binary file and writes to it. Default for trie.\n"
" after allocates anonymous memory, builds, and writes. Default for probing.\n"
"-r \"order1.arpa order2 order3 order4\" adds lower-order rest costs from these\n"
" model files. order1.arpa must be an ARPA file. All others may be ARPA or\n"
" the same data structure as being built. All files must have the same\n"
" vocabulary. For probing, the unigrams must be in the same order.\n\n"
"type is either probing or trie. Default is probing.\n\n"
"probing uses a probing hash table. It is the fastest but uses the most memory.\n"
"-p sets the space multiplier and must be >1.0. The default is 1.5.\n\n"
"trie is a straightforward trie with bit-level packing. It uses the least\n"
"memory and is still faster than SRI or IRST. Building the trie format uses an\n"
"on-disk sort to save memory.\n"
"-t is the temporary directory prefix. Default is the output file name.\n"
"-m limits memory use for sorting. Measured in MB. Default is 1024MB.\n"
"-q turns quantization on and sets the number of bits (e.g. -q 8).\n"
"-b sets backoff quantization bits. Requires -q and defaults to that value.\n"
"-a compresses pointers using an array of offsets. The parameter is the\n"
" maximum number of bits encoded by the array. Memory is minimized subject\n"
" to the maximum, so pick 255 to minimize memory.\n\n"
"Get a memory estimate by passing an ARPA file without an output file name.\n";
exit(1);
}
// I could really use boost::lexical_cast right about now.
float ParseFloat(const char *from) {
char *end;
float ret = strtod(from, &end);
if (*end) throw util::ParseNumberException(from);
return ret;
}
unsigned long int ParseUInt(const char *from) {
char *end;
unsigned long int ret = strtoul(from, &end, 10);
if (*end) throw util::ParseNumberException(from);
return ret;
}
uint8_t ParseBitCount(const char *from) {
unsigned long val = ParseUInt(from);
if (val > 25) {
util::ParseNumberException e(from);
e << " bit counts are limited to 25.";
}
return val;
}
void ParseFileList(const char *from, std::vector<std::string> &to) {
to.clear();
while (true) {
const char *i;
for (i = from; *i && *i != ' '; ++i) {}
to.push_back(std::string(from, i - from));
if (!*i) break;
from = i + 1;
}
}
void ShowSizes(const char *file, const lm::ngram::Config &config) {
std::vector<uint64_t> counts;
util::FilePiece f(file);
lm::ReadARPACounts(f, counts);
std::size_t sizes[6];
sizes[0] = ProbingModel::Size(counts, config);
sizes[1] = RestProbingModel::Size(counts, config);
sizes[2] = TrieModel::Size(counts, config);
sizes[3] = QuantTrieModel::Size(counts, config);
sizes[4] = ArrayTrieModel::Size(counts, config);
sizes[5] = QuantArrayTrieModel::Size(counts, config);
std::size_t max_length = *std::max_element(sizes, sizes + sizeof(sizes) / sizeof(size_t));
std::size_t min_length = *std::min_element(sizes, sizes + sizeof(sizes) / sizeof(size_t));
std::size_t divide;
char prefix;
if (min_length < (1 << 10) * 10) {
prefix = ' ';
divide = 1;
} else if (min_length < (1 << 20) * 10) {
prefix = 'k';
divide = 1 << 10;
} else if (min_length < (1ULL << 30) * 10) {
prefix = 'M';
divide = 1 << 20;
} else {
prefix = 'G';
divide = 1 << 30;
}
long int length = std::max<long int>(2, static_cast<long int>(ceil(log10((double) max_length / divide))));
std::cout << "Memory estimate:\ntype ";
// right align bytes.
for (long int i = 0; i < length - 2; ++i) std::cout << ' ';
std::cout << prefix << "B\n"
"probing " << std::setw(length) << (sizes[0] / divide) << " assuming -p " << config.probing_multiplier << "\n"
"probing " << std::setw(length) << (sizes[1] / divide) << " assuming -r models -p " << config.probing_multiplier << "\n"
"trie " << std::setw(length) << (sizes[2] / divide) << " without quantization\n"
"trie " << std::setw(length) << (sizes[3] / divide) << " assuming -q " << (unsigned)config.prob_bits << " -b " << (unsigned)config.backoff_bits << " quantization \n"
"trie " << std::setw(length) << (sizes[4] / divide) << " assuming -a " << (unsigned)config.pointer_bhiksha_bits << " array pointer compression\n"
"trie " << std::setw(length) << (sizes[5] / divide) << " assuming -a " << (unsigned)config.pointer_bhiksha_bits << " -q " << (unsigned)config.prob_bits << " -b " << (unsigned)config.backoff_bits<< " array pointer compression and quantization\n";
}
void ProbingQuantizationUnsupported() {
std::cerr << "Quantization is only implemented in the trie data structure." << std::endl;
exit(1);
}
} // namespace ngram
} // namespace lm
} // namespace
int main(int argc, char *argv[]) {
using namespace lm::ngram;
try {
bool quantize = false, set_backoff_bits = false, bhiksha = false, set_write_method = false, rest = false;
lm::ngram::Config config;
int opt;
while ((opt = getopt(argc, argv, "q:b:a:u:p:t:m:w:sir:")) != -1) {
switch(opt) {
case 'q':
config.prob_bits = ParseBitCount(optarg);
if (!set_backoff_bits) config.backoff_bits = config.prob_bits;
quantize = true;
break;
case 'b':
config.backoff_bits = ParseBitCount(optarg);
set_backoff_bits = true;
break;
case 'a':
config.pointer_bhiksha_bits = ParseBitCount(optarg);
bhiksha = true;
break;
case 'u':
config.unknown_missing_logprob = ParseFloat(optarg);
break;
case 'p':
config.probing_multiplier = ParseFloat(optarg);
break;
case 't':
config.temporary_directory_prefix = optarg;
break;
case 'm':
config.building_memory = ParseUInt(optarg) * 1048576;
break;
case 'w':
set_write_method = true;
if (!strcmp(optarg, "mmap")) {
config.write_method = Config::WRITE_MMAP;
} else if (!strcmp(optarg, "after")) {
config.write_method = Config::WRITE_AFTER;
} else {
Usage(argv[0]);
}
break;
case 's':
config.sentence_marker_missing = lm::SILENT;
break;
case 'i':
config.positive_log_probability = lm::SILENT;
break;
case 'r':
rest = true;
ParseFileList(optarg, config.rest_lower_files);
config.rest_function = Config::REST_LOWER;
break;
default:
Usage(argv[0]);
}
}
if (!quantize && set_backoff_bits) {
std::cerr << "You specified backoff quantization (-b) but not probability quantization (-q)" << std::endl;
abort();
}
if (optind + 1 == argc) {
ShowSizes(argv[optind], config);
return 0;
}
const char *model_type;
const char *from_file;
if (optind + 2 == argc) {
model_type = "probing";
from_file = argv[optind];
config.write_mmap = argv[optind + 1];
} else if (optind + 3 == argc) {
model_type = argv[optind];
from_file = argv[optind + 1];
config.write_mmap = argv[optind + 2];
} else {
Usage(argv[0]);
}
if (!strcmp(model_type, "probing")) {
if (!set_write_method) config.write_method = Config::WRITE_AFTER;
if (quantize || set_backoff_bits) ProbingQuantizationUnsupported();
if (rest) {
RestProbingModel(from_file, config);
} else {
ProbingModel(from_file, config);
}
} else if (!strcmp(model_type, "trie")) {
if (rest) {
std::cerr << "Rest + trie is not supported yet." << std::endl;
return 1;
}
if (!set_write_method) config.write_method = Config::WRITE_MMAP;
if (quantize) {
if (bhiksha) {
QuantArrayTrieModel(from_file, config);
} else {
QuantTrieModel(from_file, config);
}
} else {
if (bhiksha) {
ArrayTrieModel(from_file, config);
} else {
TrieModel(from_file, config);
}
}
} else {
Usage(argv[0]);
}
}
catch (const std::exception &e) {
std::cerr << e.what() << std::endl;
std::cerr << "ERROR" << std::endl;
return 1;
}
std::cerr << "SUCCESS" << std::endl;
return 0;
}
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