explosion/spaCy
1
1
Fork 0
mirror of https://github.com/explosion/spaCy.git synced 2025-11-04 09:57:26 +03:00
Code Issues Packages Projects Releases Wiki Activity

Update UD bin scripts

Browse Source 
* Update imports for `bin/`
* Add all currently supported languages
* Update subtok merger for new Matcher validation
* Modify blinded check to look at tokens instead of lemmas (for corpora
with tokens but not lemmas like Telugu)
This commit is contained in:
Adriane Boyd 2019-09-15 20:42:53 +02:00
parent 04d36d2471
commit ede32c01e2
3 changed files with 31 additions and 25 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

36
bin/ud/run_eval.py
View File

@ -7,14 +7,16 @@ import datetime
from pathlib import Path
import xml.etree.ElementTree as ET
from spacy.cli.ud import conll17_ud_eval
from spacy.cli.ud.ud_train import write_conllu
import conll17_ud_eval
from ud_train import write_conllu
from spacy.lang.lex_attrs import word_shape
from spacy.util import get_lang_class
# All languages in spaCy - in UD format (note that Norwegian is 'no' instead of 'nb')
ALL_LANGUAGES = "ar, ca, da, de, el, en, es, fa, fi, fr, ga, he, hi, hr, hu, id, " \
"it, ja, no, nl, pl, pt, ro, ru, sv, tr, ur, vi, zh"
ALL_LANGUAGES = ("af, ar, bg, bn, ca, cs, da, de, el, en, es, et, fa, fi, fr,"
"ga, he, hi, hr, hu, id, is, it, ja, kn, ko, lt, lv, mr, no,"
"nl, pl, pt, ro, ru, si, sk, sl, sq, sr, sv, ta, te, th, tl,"
"tr, tt, uk, ur, vi, zh")
# Non-parsing tasks that will be evaluated (works for default models)
EVAL_NO_PARSE = ['Tokens', 'Words', 'Lemmas', 'Sentences', 'Feats']
@ -73,10 +75,10 @@ def _contains_blinded_text(stats_xml):
tree = ET.parse(stats_xml)
root = tree.getroot()
total_tokens = int(root.find('size/total/tokens').text)
unique_lemmas = int(root.find('lemmas').get('unique'))
unique_forms = int(root.find('forms').get('unique'))
# assume the corpus is largely blinded when there are less than 1% unique tokens
return (unique_lemmas / total_tokens) < 0.01
return (unique_forms / total_tokens) < 0.01
def fetch_all_treebanks(ud_dir, languages, corpus, best_per_language):
@ -262,22 +264,26 @@ def main(out_path, ud_dir, check_parse=False, langs=ALL_LANGUAGES, exclude_train
if not exclude_trained_models:
if 'de' in models:
models['de'].append(load_model('de_core_news_sm'))
if 'es' in models:
models['es'].append(load_model('es_core_news_sm'))
models['es'].append(load_model('es_core_news_md'))
if 'pt' in models:
models['pt'].append(load_model('pt_core_news_sm'))
if 'it' in models:
models['it'].append(load_model('it_core_news_sm'))
if 'nl' in models:
models['nl'].append(load_model('nl_core_news_sm'))
models['de'].append(load_model('de_core_news_md'))
if 'el' in models:
models['el'].append(load_model('el_core_news_sm'))
models['el'].append(load_model('el_core_news_md'))
if 'en' in models:
models['en'].append(load_model('en_core_web_sm'))
models['en'].append(load_model('en_core_web_md'))
models['en'].append(load_model('en_core_web_lg'))
if 'es' in models:
models['es'].append(load_model('es_core_news_sm'))
models['es'].append(load_model('es_core_news_md'))
if 'fr' in models:
models['fr'].append(load_model('fr_core_news_sm'))
models['fr'].append(load_model('fr_core_news_md'))
if 'it' in models:
models['it'].append(load_model('it_core_news_sm'))
if 'nl' in models:
models['nl'].append(load_model('nl_core_news_sm'))
if 'pt' in models:
models['pt'].append(load_model('pt_core_news_sm'))
with out_path.open(mode='w', encoding='utf-8') as out_file:
run_all_evals(models, treebanks, out_file, check_parse, print_freq_tasks)

6
bin/ud/ud_run_test.py
View File

@ -109,15 +109,13 @@ def write_conllu(docs, file_):
merger = Matcher(docs[0].vocab)
merger.add("SUBTOK", None, [{"DEP": "subtok", "op": "+"}])
for i, doc in enumerate(docs):
matches = []
if doc.is_parsed:
matches = merger(doc)
spans = [doc[start : end + 1] for _, start, end in matches]
with doc.retokenize() as retokenizer:
for span in spans:
retokenizer.merge(span)
# TODO: This shouldn't be necessary? Should be handled in merge
for word in doc:
if word.i == word.head.i:
word.dep_ = "ROOT"
file_.write("# newdoc id = {i}\n".format(i=i))
for j, sent in enumerate(doc.sents):
file_.write("# sent_id = {i}.{j}\n".format(i=i, j=j))

10
bin/ud/ud_train.py
View File

@ -25,7 +25,7 @@ import itertools
import random
import numpy.random
from . import conll17_ud_eval
import conll17_ud_eval
from spacy import lang
from spacy.lang import zh
@ -214,6 +214,8 @@ def write_conllu(docs, file_):
merger = Matcher(docs[0].vocab)
merger.add("SUBTOK", None, [{"DEP": "subtok", "op": "+"}])
for i, doc in enumerate(docs):
matches = []
if doc.is_parsed:
matches = merger(doc)
spans = [doc[start : end + 1] for _, start, end in matches]
with doc.retokenize() as retokenizer:
@ -298,9 +300,9 @@ def get_token_conllu(token, i):
return "\n".join(lines)
Token.set_extension("get_conllu_lines", method=get_token_conllu)
Token.set_extension("begins_fused", default=False)
Token.set_extension("inside_fused", default=False)
Token.set_extension("get_conllu_lines", method=get_token_conllu, force=True)
Token.set_extension("begins_fused", default=False, force=True)
Token.set_extension("inside_fused", default=False, force=True)
##################