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authorKenneth Heafield <github@kheafield.com>2012-12-14 12:48:26 -0800
committerKenneth Heafield <github@kheafield.com>2012-12-14 12:48:26 -0800
commitdd0fdabb1db41a4230e487c80b61ace9697f150d (patch)
tree82686a3461645f83343a1926482007946d5a542c /klm/lm/model.cc
parent5d42134cc676278189b0f77708908542fbb5ccc9 (diff)
Updated kenlm
Diffstat (limited to 'klm/lm/model.cc')
-rw-r--r--klm/lm/model.cc30
1 files changed, 15 insertions, 15 deletions
diff --git a/klm/lm/model.cc b/klm/lm/model.cc
index fc61efee..a40fd2fb 100644
--- a/klm/lm/model.cc
+++ b/klm/lm/model.cc
@@ -37,7 +37,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
template <class Search, class VocabularyT> GenericModel<Search, VocabularyT>::GenericModel(const char *file, const Config &config) {
LoadLM(file, config, *this);
- // g++ prints warnings unless these are fully initialized.
+ // g++ prints warnings unless these are fully initialized.
State begin_sentence = State();
begin_sentence.length = 1;
begin_sentence.words[0] = vocab_.BeginSentence();
@@ -69,8 +69,8 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
}
template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT>::InitializeFromARPA(const char *file, const Config &config) {
- // Backing file is the ARPA. Steal it so we can make the backing file the mmap output if any.
- util::FilePiece f(backing_.file.release(), file, config.messages);
+ // Backing file is the ARPA. Steal it so we can make the backing file the mmap output if any.
+ util::FilePiece f(backing_.file.release(), file, config.ProgressMessages());
try {
std::vector<uint64_t> counts;
// File counts do not include pruned trigrams that extend to quadgrams etc. These will be fixed by search_.
@@ -80,7 +80,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
if (config.probing_multiplier <= 1.0) UTIL_THROW(ConfigException, "probing multiplier must be > 1.0");
std::size_t vocab_size = util::CheckOverflow(VocabularyT::Size(counts[0], config));
- // Setup the binary file for writing the vocab lookup table. The search_ is responsible for growing the binary file to its needs.
+ // Setup the binary file for writing the vocab lookup table. The search_ is responsible for growing the binary file to its needs.
vocab_.SetupMemory(SetupJustVocab(config, counts.size(), vocab_size, backing_), vocab_size, counts[0], config);
if (config.write_mmap) {
@@ -95,7 +95,7 @@ template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT
if (!vocab_.SawUnk()) {
assert(config.unknown_missing != THROW_UP);
- // Default probabilities for unknown.
+ // Default probabilities for unknown.
search_.UnknownUnigram().backoff = 0.0;
search_.UnknownUnigram().prob = config.unknown_missing_logprob;
}
@@ -147,7 +147,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
}
template <class Search, class VocabularyT> void GenericModel<Search, VocabularyT>::GetState(const WordIndex *context_rbegin, const WordIndex *context_rend, State &out_state) const {
- // Generate a state from context.
+ // Generate a state from context.
context_rend = std::min(context_rend, context_rbegin + P::Order() - 1);
if (context_rend == context_rbegin) {
out_state.length = 0;
@@ -191,7 +191,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
ret.rest = ptr.Rest();
ret.prob = ptr.Prob();
ret.extend_left = extend_pointer;
- // If this function is called, then it does depend on left words.
+ // If this function is called, then it does depend on left words.
ret.independent_left = false;
}
float subtract_me = ret.rest;
@@ -199,7 +199,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
next_use = extend_length;
ResumeScore(add_rbegin, add_rend, extend_length - 1, node, backoff_out, next_use, ret);
next_use -= extend_length;
- // Charge backoffs.
+ // Charge backoffs.
for (const float *b = backoff_in + ret.ngram_length - extend_length; b < backoff_in + (add_rend - add_rbegin); ++b) ret.prob += *b;
ret.prob -= subtract_me;
ret.rest -= subtract_me;
@@ -209,7 +209,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
namespace {
// Do a paraonoid copy of history, assuming new_word has already been copied
// (hence the -1). out_state.length could be zero so I avoided using
-// std::copy.
+// std::copy.
void CopyRemainingHistory(const WordIndex *from, State &out_state) {
WordIndex *out = out_state.words + 1;
const WordIndex *in_end = from + static_cast<ptrdiff_t>(out_state.length) - 1;
@@ -217,10 +217,10 @@ void CopyRemainingHistory(const WordIndex *from, State &out_state) {
}
} // namespace
-/* Ugly optimized function. Produce a score excluding backoff.
- * The search goes in increasing order of ngram length.
+/* Ugly optimized function. Produce a score excluding backoff.
+ * The search goes in increasing order of ngram length.
* Context goes backward, so context_begin is the word immediately preceeding
- * new_word.
+ * new_word.
*/
template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search, VocabularyT>::ScoreExceptBackoff(
const WordIndex *const context_rbegin,
@@ -229,7 +229,7 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
State &out_state) const {
assert(new_word < vocab_.Bound());
FullScoreReturn ret;
- // ret.ngram_length contains the last known non-blank ngram length.
+ // ret.ngram_length contains the last known non-blank ngram length.
ret.ngram_length = 1;
typename Search::Node node;
@@ -238,9 +238,9 @@ template <class Search, class VocabularyT> FullScoreReturn GenericModel<Search,
ret.prob = uni.Prob();
ret.rest = uni.Rest();
- // This is the length of the context that should be used for continuation to the right.
+ // This is the length of the context that should be used for continuation to the right.
out_state.length = HasExtension(out_state.backoff[0]) ? 1 : 0;
- // We'll write the word anyway since it will probably be used and does no harm being there.
+ // We'll write the word anyway since it will probably be used and does no harm being there.
out_state.words[0] = new_word;
if (context_rbegin == context_rend) return ret;