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#include "lm/builder/initial_probabilities.hh"
#include "lm/builder/discount.hh"
#include "lm/builder/ngram_stream.hh"
#include "lm/builder/sort.hh"
#include "lm/builder/hash_gamma.hh"
#include "util/murmur_hash.hh"
#include "util/file.hh"
#include "util/stream/chain.hh"
#include "util/stream/io.hh"
#include "util/stream/stream.hh"
#include <vector>
namespace lm { namespace builder {
namespace {
struct BufferEntry {
// Gamma from page 20 of Chen and Goodman.
float gamma;
// \sum_w a(c w) for all w.
float denominator;
};
struct HashBufferEntry : public BufferEntry {
// Hash value of ngram. Used to join contexts with backoffs.
uint64_t hash_value;
};
// Reads all entries in order like NGramStream does.
// But deletes any entries that have CutoffCount below or equal to pruning
// threshold.
class PruneNGramStream {
public:
PruneNGramStream(const util::stream::ChainPosition &position) :
current_(NULL, NGram::OrderFromSize(position.GetChain().EntrySize())),
dest_(NULL, NGram::OrderFromSize(position.GetChain().EntrySize())),
currentCount_(0),
block_(position)
{
StartBlock();
}
NGram &operator*() { return current_; }
NGram *operator->() { return ¤t_; }
operator bool() const {
return block_;
}
PruneNGramStream &operator++() {
assert(block_);
if (current_.Order() > 1) {
if(currentCount_ > 0) {
if(dest_.Base() < current_.Base()) {
memcpy(dest_.Base(), current_.Base(), current_.TotalSize());
}
dest_.NextInMemory();
}
} else {
dest_.NextInMemory();
}
current_.NextInMemory();
uint8_t *block_base = static_cast<uint8_t*>(block_->Get());
if (current_.Base() == block_base + block_->ValidSize()) {
block_->SetValidSize(dest_.Base() - block_base);
++block_;
StartBlock();
}
currentCount_ = current_.CutoffCount();
return *this;
}
private:
void StartBlock() {
for (; ; ++block_) {
if (!block_) return;
if (block_->ValidSize()) break;
}
current_.ReBase(block_->Get());
currentCount_ = current_.CutoffCount();
dest_.ReBase(block_->Get());
}
NGram current_; // input iterator
NGram dest_; // output iterator
uint64_t currentCount_;
util::stream::Link block_;
};
// Extract an array of HashedGamma from an array of BufferEntry.
class OnlyGamma {
public:
OnlyGamma(bool pruning) : pruning_(pruning) {}
void Run(const util::stream::ChainPosition &position) {
for (util::stream::Link block_it(position); block_it; ++block_it) {
if(pruning_) {
const HashBufferEntry *in = static_cast<const HashBufferEntry*>(block_it->Get());
const HashBufferEntry *end = static_cast<const HashBufferEntry*>(block_it->ValidEnd());
// Just make it point to the beginning of the stream so it can be overwritten
// With HashGamma values. Do not attempt to interpret the values until set below.
HashGamma *out = static_cast<HashGamma*>(block_it->Get());
for (; in < end; out += 1, in += 1) {
// buffering, otherwise might overwrite values too early
float gamma_buf = in->gamma;
uint64_t hash_buf = in->hash_value;
out->gamma = gamma_buf;
out->hash_value = hash_buf;
}
block_it->SetValidSize((block_it->ValidSize() * sizeof(HashGamma)) / sizeof(HashBufferEntry));
}
else {
float *out = static_cast<float*>(block_it->Get());
const float *in = out;
const float *end = static_cast<const float*>(block_it->ValidEnd());
for (out += 1, in += 2; in < end; out += 1, in += 2) {
*out = *in;
}
block_it->SetValidSize(block_it->ValidSize() / 2);
}
}
}
private:
bool pruning_;
};
class AddRight {
public:
AddRight(const Discount &discount, const util::stream::ChainPosition &input, bool pruning)
: discount_(discount), input_(input), pruning_(pruning) {}
void Run(const util::stream::ChainPosition &output) {
NGramStream in(input_);
util::stream::Stream out(output);
std::vector<WordIndex> previous(in->Order() - 1);
// Silly windows requires this workaround to just get an invalid pointer when empty.
void *const previous_raw = previous.empty() ? NULL : static_cast<void*>(&previous[0]);
const std::size_t size = sizeof(WordIndex) * previous.size();
for(; in; ++out) {
memcpy(previous_raw, in->begin(), size);
uint64_t denominator = 0;
uint64_t normalizer = 0;
uint64_t counts[4];
memset(counts, 0, sizeof(counts));
do {
denominator += in->UnmarkedCount();
// Collect unused probability mass from pruning.
// Becomes 0 for unpruned ngrams.
normalizer += in->UnmarkedCount() - in->CutoffCount();
// Chen&Goodman do not mention counting based on cutoffs, but
// backoff becomes larger than 1 otherwise, so probably needs
// to count cutoffs. Counts normally without pruning.
if(in->CutoffCount() > 0)
++counts[std::min(in->CutoffCount(), static_cast<uint64_t>(3))];
} while (++in && !memcmp(previous_raw, in->begin(), size));
BufferEntry &entry = *reinterpret_cast<BufferEntry*>(out.Get());
entry.denominator = static_cast<float>(denominator);
entry.gamma = 0.0;
for (unsigned i = 1; i <= 3; ++i) {
entry.gamma += discount_.Get(i) * static_cast<float>(counts[i]);
}
// Makes model sum to 1 with pruning (I hope).
entry.gamma += normalizer;
entry.gamma /= entry.denominator;
if(pruning_) {
// If pruning is enabled the stream actually contains HashBufferEntry, see InitialProbabilities(...),
// so add a hash value that identifies the current ngram.
static_cast<HashBufferEntry*>(&entry)->hash_value = util::MurmurHashNative(previous_raw, size);
}
}
out.Poison();
}
private:
const Discount &discount_;
const util::stream::ChainPosition input_;
bool pruning_;
};
class MergeRight {
public:
MergeRight(bool interpolate_unigrams, const util::stream::ChainPosition &from_adder, const Discount &discount)
: interpolate_unigrams_(interpolate_unigrams), from_adder_(from_adder), discount_(discount) {}
// calculate the initial probability of each n-gram (before order-interpolation)
// Run() gets invoked once for each order
void Run(const util::stream::ChainPosition &primary) {
util::stream::Stream summed(from_adder_);
PruneNGramStream grams(primary);
// Without interpolation, the interpolation weight goes to <unk>.
if (grams->Order() == 1 && !interpolate_unigrams_) {
BufferEntry sums(*static_cast<const BufferEntry*>(summed.Get()));
assert(*grams->begin() == kUNK);
grams->Value().uninterp.prob = sums.gamma;
grams->Value().uninterp.gamma = 0.0;
while (++grams) {
grams->Value().uninterp.prob = discount_.Apply(grams->Count()) / sums.denominator;
grams->Value().uninterp.gamma = 0.0;
}
++summed;
return;
}
std::vector<WordIndex> previous(grams->Order() - 1);
const std::size_t size = sizeof(WordIndex) * previous.size();
for (; grams; ++summed) {
memcpy(&previous[0], grams->begin(), size);
const BufferEntry &sums = *static_cast<const BufferEntry*>(summed.Get());
do {
Payload &pay = grams->Value();
pay.uninterp.prob = discount_.Apply(grams->UnmarkedCount()) / sums.denominator;
pay.uninterp.gamma = sums.gamma;
} while (++grams && !memcmp(&previous[0], grams->begin(), size));
}
}
private:
bool interpolate_unigrams_;
util::stream::ChainPosition from_adder_;
Discount discount_;
};
} // namespace
void InitialProbabilities(
const InitialProbabilitiesConfig &config,
const std::vector<Discount> &discounts,
util::stream::Chains &primary,
util::stream::Chains &second_in,
util::stream::Chains &gamma_out,
const std::vector<uint64_t> &prune_thresholds) {
for (size_t i = 0; i < primary.size(); ++i) {
util::stream::ChainConfig gamma_config = config.adder_out;
if(prune_thresholds[i] > 0)
gamma_config.entry_size = sizeof(HashBufferEntry);
else
gamma_config.entry_size = sizeof(BufferEntry);
util::stream::ChainPosition second(second_in[i].Add());
second_in[i] >> util::stream::kRecycle;
gamma_out.push_back(gamma_config);
gamma_out[i] >> AddRight(discounts[i], second, prune_thresholds[i] > 0);
primary[i] >> MergeRight(config.interpolate_unigrams, gamma_out[i].Add(), discounts[i]);
// Don't bother with the OnlyGamma thread for something to discard.
if (i) gamma_out[i] >> OnlyGamma(prune_thresholds[i] > 0);
}
}
}} // namespaces
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