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https://github.com/explosion/spaCy.git
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* Cut down init_model to work on more languages
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@ -29,8 +29,6 @@ from shutil import copytree
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import codecs
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from collections import defaultdict
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from spacy.en import get_lex_props
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from spacy.en.lemmatizer import Lemmatizer
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from spacy.vocab import Vocab
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from spacy.vocab import write_binary_vectors
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from spacy.strings import hash_string
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@ -38,6 +36,11 @@ from preshed.counter import PreshCounter
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from spacy.parts_of_speech import NOUN, VERB, ADJ
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import spacy.en
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import spacy.de
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def setup_tokenizer(lang_data_dir, tok_dir):
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if not tok_dir.exists():
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@ -139,7 +142,7 @@ def _read_senses(loc):
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return lexicon
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def setup_vocab(src_dir, dst_dir):
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def setup_vocab(get_lex_attr, src_dir, dst_dir):
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if not dst_dir.exists():
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dst_dir.mkdir()
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@ -148,13 +151,13 @@ def setup_vocab(src_dir, dst_dir):
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write_binary_vectors(str(vectors_src), str(dst_dir / 'vec.bin'))
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else:
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print("Warning: Word vectors file not found")
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vocab = Vocab(data_dir=None, get_lex_props=get_lex_props)
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vocab = Vocab(data_dir=None, get_lex_attr=get_lex_attr)
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clusters = _read_clusters(src_dir / 'clusters.txt')
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probs, oov_prob = _read_probs(src_dir / 'words.sgt.prob')
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if not probs:
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probs, oov_prob = _read_freqs(src_dir / 'freqs.txt')
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if not probs:
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oov_prob = 0.0
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oov_prob = -20
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else:
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oov_prob = min(probs.values())
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for word in clusters:
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@ -163,23 +166,30 @@ def setup_vocab(src_dir, dst_dir):
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lexicon = []
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for word, prob in reversed(sorted(list(probs.items()), key=lambda item: item[1])):
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entry = get_lex_props(word)
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entry['prob'] = float(prob)
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cluster = clusters.get(word, '0')
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lexeme = vocab[word]
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lexeme.prob = prob
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lexeme.is_oov = False
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# Decode as a little-endian string, so that we can do & 15 to get
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# the first 4 bits. See _parse_features.pyx
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entry['cluster'] = int(cluster[::-1], 2)
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vocab[word] = entry
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if word in clusters:
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lexeme.cluster = int(clusters[word][::-1], 2)
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else:
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lexeme.cluster = 0
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vocab.dump(str(dst_dir / 'lexemes.bin'))
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vocab.strings.dump(str(dst_dir / 'strings.txt'))
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with (dst_dir / 'oov_prob').open('w') as file_:
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file_.write('%f' % oov_prob)
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def main(lang_data_dir, corpora_dir, model_dir):
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def main(lang_id, lang_data_dir, corpora_dir, model_dir):
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languages = {
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'en': spacy.en.get_lex_attr,
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'de': spacy.en.get_lex_attr
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}
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model_dir = Path(model_dir)
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lang_data_dir = Path(lang_data_dir)
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corpora_dir = Path(corpora_dir)
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lang_data_dir = Path(lang_data_dir) / lang_id
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corpora_dir = Path(corpora_dir) / lang_id
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assert corpora_dir.exists()
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assert lang_data_dir.exists()
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@ -188,12 +198,12 @@ def main(lang_data_dir, corpora_dir, model_dir):
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model_dir.mkdir()
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setup_tokenizer(lang_data_dir, model_dir / 'tokenizer')
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setup_vocab(corpora_dir, model_dir / 'vocab')
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setup_vocab(languages[lang_id], corpora_dir, model_dir / 'vocab')
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if (lang_data_dir / 'gazetteer.json').exists():
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copyfile(str(lang_data_dir / 'gazetteer.json'),
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str(model_dir / 'vocab' / 'gazetteer.json'))
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if not (model_dir / 'wordnet').exists():
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if not (model_dir / 'wordnet').exists() and (corpora_dir / 'wordnet').exists():
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copytree(str(corpora_dir / 'wordnet' / 'dict'), str(model_dir / 'wordnet'))
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