spaCy/spacy/cli/vocab.py
2017-10-30 16:19:22 +01:00

49 lines
1.7 KiB
Python

'''Compile a vocabulary from a lexicon jsonl file and word vectors.'''
# coding: utf8
from __future__ import unicode_literals
from pathlib import Path
import plac
import json
import spacy
import numpy
from spacy.util import ensure_path
@plac.annotations(
lang=("model language", "positional", None, str),
output_dir=("output directory to store model in", "positional", None, str),
lexemes_loc=("location of JSONL-formatted lexical data", "positional",
None, str),
vectors_loc=("location of vectors data, as numpy .npz (optional)",
"positional", None, str),
version=("Model version", "option", "V", str),
)
def make_vocab(lang, output_dir, lexemes_loc, vectors_loc=None, version=None):
out_dir = ensure_path(output_dir)
jsonl_loc = ensure_path(lexemes_loc)
nlp = spacy.blank(lang)
for word in nlp.vocab:
word.rank = 0
with jsonl_loc.open() as file_:
for line in file_:
if line.strip():
attrs = json.loads(line)
if 'settings' in attrs:
nlp.vocab.cfg.update(attrs['settings'])
else:
lex = nlp.vocab[attrs['orth']]
lex.set_attrs(**attrs)
assert lex.rank == attrs['id']
if vectors_loc is not None:
vector_data = numpy.load(open(vectors_loc, 'rb'))
nlp.vocab.clear_vectors(width=vector_data.shape[1])
added = 0
for word in nlp.vocab:
if word.rank:
nlp.vocab.vectors.add(word.orth_, row=word.rank,
vector=vector_data[word.rank])
added += 1
nlp.to_disk(out_dir)
return nlp