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spaCy
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* Cut down init_model to work on more languages

This commit is contained in:
Matthew Honnibal 2015-08-24 01:05:20 +02:00
parent 5d5922dbfa
commit bbf07ac253
1 changed files with 25 additions and 15 deletions
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40
bin/init_model.py
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@ -29,8 +29,6 @@ from shutil import copytree
import codecs import codecs
from collections import defaultdict from collections import defaultdict
from spacy.en import get_lex_props
from spacy.en.lemmatizer import Lemmatizer
from spacy.vocab import Vocab from spacy.vocab import Vocab
from spacy.vocab import write_binary_vectors from spacy.vocab import write_binary_vectors
from spacy.strings import hash_string from spacy.strings import hash_string
@ -38,6 +36,11 @@ from preshed.counter import PreshCounter
from spacy.parts_of_speech import NOUN, VERB, ADJ from spacy.parts_of_speech import NOUN, VERB, ADJ
import spacy.en
import spacy.de
def setup_tokenizer(lang_data_dir, tok_dir): def setup_tokenizer(lang_data_dir, tok_dir):
if not tok_dir.exists(): if not tok_dir.exists():
@ -139,7 +142,7 @@ def _read_senses(loc):
return lexicon return lexicon
def setup_vocab(src_dir, dst_dir): def setup_vocab(get_lex_attr, src_dir, dst_dir):
if not dst_dir.exists(): if not dst_dir.exists():
dst_dir.mkdir() dst_dir.mkdir()
@ -148,13 +151,13 @@ def setup_vocab(src_dir, dst_dir):
write_binary_vectors(str(vectors_src), str(dst_dir / 'vec.bin')) write_binary_vectors(str(vectors_src), str(dst_dir / 'vec.bin'))
else: else:
print("Warning: Word vectors file not found") print("Warning: Word vectors file not found")
vocab = Vocab(data_dir=None, get_lex_props=get_lex_props) vocab = Vocab(data_dir=None, get_lex_attr=get_lex_attr)
clusters = _read_clusters(src_dir / 'clusters.txt') clusters = _read_clusters(src_dir / 'clusters.txt')
probs, oov_prob = _read_probs(src_dir / 'words.sgt.prob') probs, oov_prob = _read_probs(src_dir / 'words.sgt.prob')
if not probs: if not probs:
probs, oov_prob = _read_freqs(src_dir / 'freqs.txt') probs, oov_prob = _read_freqs(src_dir / 'freqs.txt')
if not probs: if not probs:
oov_prob = 0.0 oov_prob = -20
else: else:
oov_prob = min(probs.values()) oov_prob = min(probs.values())
for word in clusters: for word in clusters:
@ -163,23 +166,30 @@ def setup_vocab(src_dir, dst_dir):
lexicon = [] lexicon = []
for word, prob in reversed(sorted(list(probs.items()), key=lambda item: item[1])): for word, prob in reversed(sorted(list(probs.items()), key=lambda item: item[1])):
entry = get_lex_props(word) lexeme = vocab[word]
entry['prob'] = float(prob) lexeme.prob = prob
cluster = clusters.get(word, '0') lexeme.is_oov = False
# Decode as a little-endian string, so that we can do & 15 to get # Decode as a little-endian string, so that we can do & 15 to get
# the first 4 bits. See _parse_features.pyx # the first 4 bits. See _parse_features.pyx
entry['cluster'] = int(cluster[::-1], 2) if word in clusters:
vocab[word] = entry lexeme.cluster = int(clusters[word][::-1], 2)
else:
lexeme.cluster = 0
vocab.dump(str(dst_dir / 'lexemes.bin')) vocab.dump(str(dst_dir / 'lexemes.bin'))
vocab.strings.dump(str(dst_dir / 'strings.txt')) vocab.strings.dump(str(dst_dir / 'strings.txt'))
with (dst_dir / 'oov_prob').open('w') as file_: with (dst_dir / 'oov_prob').open('w') as file_:
file_.write('%f' % oov_prob) file_.write('%f' % oov_prob)
def main(lang_data_dir, corpora_dir, model_dir): def main(lang_id, lang_data_dir, corpora_dir, model_dir):
languages = {
'en': spacy.en.get_lex_attr,
'de': spacy.en.get_lex_attr
}
model_dir = Path(model_dir) model_dir = Path(model_dir)
lang_data_dir = Path(lang_data_dir) lang_data_dir = Path(lang_data_dir) / lang_id
corpora_dir = Path(corpora_dir) corpora_dir = Path(corpora_dir) / lang_id
assert corpora_dir.exists() assert corpora_dir.exists()
assert lang_data_dir.exists() assert lang_data_dir.exists()
@ -188,12 +198,12 @@ def main(lang_data_dir, corpora_dir, model_dir):
model_dir.mkdir() model_dir.mkdir()
setup_tokenizer(lang_data_dir, model_dir / 'tokenizer') setup_tokenizer(lang_data_dir, model_dir / 'tokenizer')
setup_vocab(corpora_dir, model_dir / 'vocab') setup_vocab(languages[lang_id], corpora_dir, model_dir / 'vocab')
if (lang_data_dir / 'gazetteer.json').exists(): if (lang_data_dir / 'gazetteer.json').exists():
copyfile(str(lang_data_dir / 'gazetteer.json'), copyfile(str(lang_data_dir / 'gazetteer.json'),
str(model_dir / 'vocab' / 'gazetteer.json')) str(model_dir / 'vocab' / 'gazetteer.json'))
if not (model_dir / 'wordnet').exists(): if not (model_dir / 'wordnet').exists() and (corpora_dir / 'wordnet').exists():
copytree(str(corpora_dir / 'wordnet' / 'dict'), str(model_dir / 'wordnet')) copytree(str(corpora_dir / 'wordnet' / 'dict'), str(model_dir / 'wordnet'))