File size: 7,714 Bytes
8652957 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 |
#include "lm/interpolate/pipeline.hh"
#include "lm/common/compare.hh"
#include "lm/common/print.hh"
#include "lm/common/renumber.hh"
#include "lm/vocab.hh"
#include "lm/interpolate/backoff_reunification.hh"
#include "lm/interpolate/interpolate_info.hh"
#include "lm/interpolate/merge_probabilities.hh"
#include "lm/interpolate/merge_vocab.hh"
#include "lm/interpolate/normalize.hh"
#include "lm/interpolate/universal_vocab.hh"
#include "util/stream/chain.hh"
#include "util/stream/count_records.hh"
#include "util/stream/io.hh"
#include "util/stream/multi_stream.hh"
#include "util/stream/sort.hh"
#include "util/fixed_array.hh"
namespace lm { namespace interpolate { namespace {
/* Put the original input files on chains and renumber them */
void SetupInputs(std::size_t buffer_size, const UniversalVocab &vocab, util::FixedArray<ModelBuffer> &models, bool exclude_highest, util::FixedArray<util::stream::Chains> &chains, util::FixedArray<util::stream::ChainPositions> &positions) {
chains.clear();
positions.clear();
// TODO: much better memory sizing heuristics e.g. not making the chain larger than it will use.
util::stream::ChainConfig config(0, 2, buffer_size);
for (std::size_t i = 0; i < models.size(); ++i) {
chains.push_back(models[i].Order() - exclude_highest);
for (std::size_t j = 0; j < models[i].Order() - exclude_highest; ++j) {
config.entry_size = sizeof(WordIndex) * (j + 1) + sizeof(float) * 2; // TODO do not include wasteful backoff for highest.
chains.back().push_back(config);
}
if (i == models.size() - 1)
chains.back().back().ActivateProgress();
models[i].Source(chains.back());
for (std::size_t j = 0; j < models[i].Order() - exclude_highest; ++j) {
chains[i][j] >> Renumber(vocab.Mapping(i), j + 1);
}
}
for (std::size_t i = 0; i < chains.size(); ++i) {
positions.push_back(chains[i]);
}
}
template <class Compare> void SinkSort(const util::stream::SortConfig &config, util::stream::Chains &chains, util::stream::Sorts<Compare> &sorts) {
for (std::size_t i = 0; i < chains.size(); ++i) {
sorts.push_back(chains[i], config, Compare(i + 1));
}
}
template <class Compare> void SourceSort(util::stream::Chains &chains, util::stream::Sorts<Compare> &sorts) {
// TODO memory management
for (std::size_t i = 0; i < sorts.size(); ++i) {
sorts[i].Merge(sorts[i].DefaultLazy());
}
for (std::size_t i = 0; i < sorts.size(); ++i) {
sorts[i].Output(chains[i], sorts[i].DefaultLazy());
}
}
} // namespace
void Pipeline(util::FixedArray<ModelBuffer> &models, const Config &config, int write_file) {
// Setup InterpolateInfo and UniversalVocab.
InterpolateInfo info;
info.lambdas = config.lambdas;
std::vector<WordIndex> vocab_sizes;
util::scoped_fd vocab_null(util::MakeTemp(config.sort.temp_prefix));
std::size_t max_order = 0;
util::FixedArray<int> vocab_files(models.size());
for (ModelBuffer *i = models.begin(); i != models.end(); ++i) {
info.orders.push_back(i->Order());
vocab_sizes.push_back(i->Counts()[0]);
vocab_files.push_back(i->VocabFile());
max_order = std::max(max_order, i->Order());
}
util::scoped_ptr<UniversalVocab> vocab(new UniversalVocab(vocab_sizes));
{
ngram::ImmediateWriteWordsWrapper writer(NULL, vocab_null.get(), 0);
MergeVocab(vocab_files, *vocab, writer);
}
std::cerr << "Merging probabilities." << std::endl;
// Pass 1: merge probabilities
util::FixedArray<util::stream::Chains> input_chains(models.size());
util::FixedArray<util::stream::ChainPositions> models_by_order(models.size());
SetupInputs(config.BufferSize(), *vocab, models, false, input_chains, models_by_order);
util::stream::Chains merged_probs(max_order);
for (std::size_t i = 0; i < max_order; ++i) {
merged_probs.push_back(util::stream::ChainConfig(PartialProbGamma::TotalSize(info, i + 1), 2, config.BufferSize())); // TODO: not buffer_size
}
merged_probs >> MergeProbabilities(info, models_by_order);
std::vector<uint64_t> counts(max_order);
for (std::size_t i = 0; i < max_order; ++i) {
merged_probs[i] >> util::stream::CountRecords(&counts[i]);
}
for (util::stream::Chains *i = input_chains.begin(); i != input_chains.end(); ++i) {
*i >> util::stream::kRecycle;
}
// Pass 2: normalize.
{
util::stream::Sorts<ContextOrder> sorts(merged_probs.size());
SinkSort(config.sort, merged_probs, sorts);
merged_probs.Wait(true);
for (util::stream::Chains *i = input_chains.begin(); i != input_chains.end(); ++i) {
i->Wait(true);
}
SourceSort(merged_probs, sorts);
}
std::cerr << "Normalizing" << std::endl;
SetupInputs(config.BufferSize(), *vocab, models, true, input_chains, models_by_order);
util::stream::Chains probabilities(max_order), backoffs(max_order - 1);
std::size_t block_count = 2;
for (std::size_t i = 0; i < max_order; ++i) {
// Careful accounting to ensure RewindableStream can fit the entire vocabulary.
block_count = std::max<std::size_t>(block_count, 2);
// This much needs to fit in RewindableStream.
std::size_t fit = NGram<float>::TotalSize(i + 1) * counts[0];
// fit / (block_count - 1) rounded up
std::size_t min_block = (fit + block_count - 2) / (block_count - 1);
std::size_t specify = std::max(config.BufferSize(), min_block * block_count);
probabilities.push_back(util::stream::ChainConfig(NGram<float>::TotalSize(i + 1), block_count, specify));
}
for (std::size_t i = 0; i < max_order - 1; ++i) {
backoffs.push_back(util::stream::ChainConfig(sizeof(float), 2, config.BufferSize()));
}
Normalize(info, models_by_order, merged_probs, probabilities, backoffs);
util::FixedArray<util::stream::FileBuffer> backoff_buffers(backoffs.size());
for (std::size_t i = 0; i < max_order - 1; ++i) {
backoff_buffers.push_back(util::MakeTemp(config.sort.temp_prefix));
backoffs[i] >> backoff_buffers.back().Sink() >> util::stream::kRecycle;
}
for (util::stream::Chains *i = input_chains.begin(); i != input_chains.end(); ++i) {
*i >> util::stream::kRecycle;
}
merged_probs >> util::stream::kRecycle;
// Pass 3: backoffs in the right place.
{
util::stream::Sorts<SuffixOrder> sorts(probabilities.size());
SinkSort(config.sort, probabilities, sorts);
probabilities.Wait(true);
for (util::stream::Chains *i = input_chains.begin(); i != input_chains.end(); ++i) {
i->Wait(true);
}
backoffs.Wait(true);
merged_probs.Wait(true);
// destroy universal vocab to save RAM.
vocab.reset();
SourceSort(probabilities, sorts);
}
std::cerr << "Reunifying backoffs" << std::endl;
util::stream::ChainPositions prob_pos(max_order - 1);
util::stream::Chains combined(max_order - 1);
for (std::size_t i = 0; i < max_order - 1; ++i) {
if (i == max_order - 2)
backoffs[i].ActivateProgress();
backoffs[i].SetProgressTarget(backoff_buffers[i].Size());
backoffs[i] >> backoff_buffers[i].Source(true);
prob_pos.push_back(probabilities[i].Add());
combined.push_back(util::stream::ChainConfig(NGram<ProbBackoff>::TotalSize(i + 1), 2, config.BufferSize()));
}
util::stream::ChainPositions backoff_pos(backoffs);
ReunifyBackoff(prob_pos, backoff_pos, combined);
util::stream::ChainPositions output_pos(max_order);
for (std::size_t i = 0; i < max_order - 1; ++i) {
output_pos.push_back(combined[i].Add());
}
output_pos.push_back(probabilities.back().Add());
probabilities >> util::stream::kRecycle;
backoffs >> util::stream::kRecycle;
combined >> util::stream::kRecycle;
// TODO genericize to ModelBuffer etc.
PrintARPA(vocab_null.get(), write_file, counts).Run(output_pos);
}
}} // namespaces
|