spaCy/spacy/cli/vocab.py

55 lines
2.0 KiB
Python

# coding: utf8
from __future__ import unicode_literals
import plac
import json
import spacy
import numpy
from pathlib import Path
from ..util import prints, ensure_path
@plac.annotations(
lang=("model language", "positional", None, str),
output_dir=("model output directory", "positional", None, Path),
lexemes_loc=("location of JSONL-formatted lexical data", "positional",
None, Path),
vectors_loc=("optional: location of vectors data, as numpy .npz",
"positional", None, str))
def make_vocab(cmd, lang, output_dir, lexemes_loc, vectors_loc=None):
"""Compile a vocabulary from a lexicon jsonl file and word vectors."""
if not lexemes_loc.exists():
prints(lexemes_loc, title="Can't find lexical data", exits=1)
vectors_loc = ensure_path(vectors_loc)
nlp = spacy.blank(lang)
for word in nlp.vocab:
word.rank = 0
lex_added = 0
vec_added = 0
with lexemes_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']
lex_added += 1
if vectors_loc is not None:
vector_data = numpy.load(open(vectors_loc, 'rb'))
nlp.vocab.clear_vectors(width=vector_data.shape[1])
for word in nlp.vocab:
if word.rank:
nlp.vocab.vectors.add(word.orth_, row=word.rank,
vector=vector_data[word.rank])
vec_added += 1
if not output_dir.exists():
output_dir.mkdir()
nlp.to_disk(output_dir)
prints("{} entries, {} vectors".format(lex_added, vec_added), output_dir,
title="Sucessfully compiled vocab and vectors, and saved model")
return nlp