コード例 #1
0
ファイル: translation_model.py プロジェクト: lrjxgl/seq2seq-1
 def read_vocab(self):
     # don't try reading vocabulary for encoders that take pre-computed features
     self.vocabs = [
         None if binary else utils.initialize_vocabulary(vocab_path)
         for vocab_path, binary in zip(self.filenames.vocab, self.binary)
     ]
     self.src_vocab, self.trg_vocab = self.vocabs[:len(self.src_ext)], self.vocabs[len(self.src_ext):]
コード例 #2
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 def read_vocab(self):
     # don't try reading vocabulary for encoders that take pre-computed features
     # [({key:val, key:val,....}, [word, word, ...., word]), (), (), () ,....., ()]
     self.vocabs = [
         None if binary else utils.initialize_vocabulary(vocab_path)
         for vocab_path, binary in zip(self.filenames.vocab, self.binary)
     ]
     # trg_vocab: [(name1: {key:val, key:val,....}, name2:[word, word, ...., word])]
     self.src_vocab, self.trg_vocab = self.vocabs[:len(self.src_ext)], self.vocabs[len(self.src_ext):]
コード例 #3
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 def _read_vocab(self):
     # don't try reading vocabulary for encoders that take pre-computed features
     self.vocabs = [
         utils.initialize_vocabulary(vocab_path) if not binary else None
         for ext, vocab_path, binary in zip(
             self.extensions, self.filenames.vocab, self.binary_input)
     ]
     self.src_vocab = self.vocabs[:-1]
     self.trg_vocab = self.vocabs[-1]
     self.ngrams = self.filenames.lm_path and utils.read_ngrams(
         self.filenames.lm_path, self.trg_vocab.vocab)