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authorWu, Ke <wuke@cs.umd.edu>2014-12-17 16:15:13 -0500
committerWu, Ke <wuke@cs.umd.edu>2014-12-17 16:15:13 -0500
commit6829a0bc624b02ebefc79f8cf9ec89d7d64a7c30 (patch)
tree125dfb20f73342873476c793995397b26fd202dd /klm/lm/read_arpa.hh
parentb455a108a21f4ba5a58ab1bc53a8d2bf4d829067 (diff)
parent7468e8d85e99b4619442c7afaf4a0d92870111bb (diff)
Merge branch 'const_reorder_2' into softsyn_2
Diffstat (limited to 'klm/lm/read_arpa.hh')
-rw-r--r--klm/lm/read_arpa.hh31
1 files changed, 18 insertions, 13 deletions
diff --git a/klm/lm/read_arpa.hh b/klm/lm/read_arpa.hh
index 234d130c..64eeef30 100644
--- a/klm/lm/read_arpa.hh
+++ b/klm/lm/read_arpa.hh
@@ -1,5 +1,5 @@
-#ifndef LM_READ_ARPA__
-#define LM_READ_ARPA__
+#ifndef LM_READ_ARPA_H
+#define LM_READ_ARPA_H
#include "lm/lm_exception.hh"
#include "lm/word_index.hh"
@@ -28,7 +28,7 @@ void ReadEnd(util::FilePiece &in);
extern const bool kARPASpaces[256];
-// Positive log probability warning.
+// Positive log probability warning.
class PositiveProbWarn {
public:
PositiveProbWarn() : action_(THROW_UP) {}
@@ -48,17 +48,17 @@ template <class Voc, class Weights> void Read1Gram(util::FilePiece &f, Voc &voca
warn.Warn(prob);
prob = 0.0;
}
- if (f.get() != '\t') UTIL_THROW(FormatLoadException, "Expected tab after probability");
- Weights &value = unigrams[vocab.Insert(f.ReadDelimited(kARPASpaces))];
- value.prob = prob;
- ReadBackoff(f, value);
+ UTIL_THROW_IF(f.get() != '\t', FormatLoadException, "Expected tab after probability");
+ WordIndex word = vocab.Insert(f.ReadDelimited(kARPASpaces));
+ Weights &w = unigrams[word];
+ w.prob = prob;
+ ReadBackoff(f, w);
} catch(util::Exception &e) {
e << " in the 1-gram at byte " << f.Offset();
throw;
}
}
-// Return true if a positive log probability came out.
template <class Voc, class Weights> void Read1Grams(util::FilePiece &f, std::size_t count, Voc &vocab, Weights *unigrams, PositiveProbWarn &warn) {
ReadNGramHeader(f, 1);
for (std::size_t i = 0; i < count; ++i) {
@@ -67,16 +67,21 @@ template <class Voc, class Weights> void Read1Grams(util::FilePiece &f, std::siz
vocab.FinishedLoading(unigrams);
}
-// Return true if a positive log probability came out.
-template <class Voc, class Weights> void ReadNGram(util::FilePiece &f, const unsigned char n, const Voc &vocab, WordIndex *const reverse_indices, Weights &weights, PositiveProbWarn &warn) {
+// Read ngram, write vocab ids to indices_out.
+template <class Voc, class Weights, class Iterator> void ReadNGram(util::FilePiece &f, const unsigned char n, const Voc &vocab, Iterator indices_out, Weights &weights, PositiveProbWarn &warn) {
try {
weights.prob = f.ReadFloat();
if (weights.prob > 0.0) {
warn.Warn(weights.prob);
weights.prob = 0.0;
}
- for (WordIndex *vocab_out = reverse_indices + n - 1; vocab_out >= reverse_indices; --vocab_out) {
- *vocab_out = vocab.Index(f.ReadDelimited(kARPASpaces));
+ for (unsigned char i = 0; i < n; ++i, ++indices_out) {
+ StringPiece word(f.ReadDelimited(kARPASpaces));
+ WordIndex index = vocab.Index(word);
+ *indices_out = index;
+ // Check for words mapped to <unk> that are not the string <unk>.
+ UTIL_THROW_IF(index == 0 /* mapped to <unk> */ && (word != StringPiece("<unk>", 5)) && (word != StringPiece("<UNK>", 5)),
+ FormatLoadException, "Word " << word << " was not seen in the unigrams (which are supposed to list the entire vocabulary) but appears");
}
ReadBackoff(f, weights);
} catch(util::Exception &e) {
@@ -87,4 +92,4 @@ template <class Voc, class Weights> void ReadNGram(util::FilePiece &f, const uns
} // namespace lm
-#endif // LM_READ_ARPA__
+#endif // LM_READ_ARPA_H