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