mirror of
https://github.com/explosion/spaCy.git
synced 2025-07-01 10:23:07 +03:00
Fix morphology task in ud-train
This commit is contained in:
parent
1f9f834dc0
commit
f03640b41f
|
@ -84,10 +84,12 @@ def read_data(nlp, conllu_file, text_file, raw_text=True, oracle_segments=False,
|
||||||
if oracle_segments:
|
if oracle_segments:
|
||||||
docs.append(Doc(nlp.vocab, words=sent['words'], spaces=sent['spaces']))
|
docs.append(Doc(nlp.vocab, words=sent['words'], spaces=sent['spaces']))
|
||||||
golds.append(GoldParse(docs[-1], **sent))
|
golds.append(GoldParse(docs[-1], **sent))
|
||||||
|
assert golds[-1].morphology is not None
|
||||||
|
|
||||||
sent_annots.append(sent)
|
sent_annots.append(sent)
|
||||||
if raw_text and max_doc_length and len(sent_annots) >= max_doc_length:
|
if raw_text and max_doc_length and len(sent_annots) >= max_doc_length:
|
||||||
doc, gold = _make_gold(nlp, None, sent_annots)
|
doc, gold = _make_gold(nlp, None, sent_annots)
|
||||||
|
assert gold.morphology is not None
|
||||||
sent_annots = []
|
sent_annots = []
|
||||||
docs.append(doc)
|
docs.append(doc)
|
||||||
golds.append(gold)
|
golds.append(gold)
|
||||||
|
@ -104,12 +106,13 @@ def read_data(nlp, conllu_file, text_file, raw_text=True, oracle_segments=False,
|
||||||
|
|
||||||
def _parse_morph_string(morph_string):
|
def _parse_morph_string(morph_string):
|
||||||
if morph_string == '_':
|
if morph_string == '_':
|
||||||
return None
|
return set()
|
||||||
output = []
|
output = []
|
||||||
replacements = {'1': 'one', '2': 'two', '3': 'three'}
|
replacements = {'1': 'one', '2': 'two', '3': 'three'}
|
||||||
for feature in morph_string.split('|'):
|
for feature in morph_string.split('|'):
|
||||||
key, value = feature.split('=')
|
key, value = feature.split('=')
|
||||||
value = replacements.get(value, value)
|
value = replacements.get(value, value)
|
||||||
|
value = value.split(',')[0]
|
||||||
output.append('%s_%s' % (key, value.lower()))
|
output.append('%s_%s' % (key, value.lower()))
|
||||||
return set(output)
|
return set(output)
|
||||||
|
|
||||||
|
@ -146,7 +149,7 @@ def _make_gold(nlp, text, sent_annots, drop_deps=0.0):
|
||||||
sent_starts = []
|
sent_starts = []
|
||||||
for sent in sent_annots:
|
for sent in sent_annots:
|
||||||
flat['heads'].extend(len(flat['words'])+head for head in sent['heads'])
|
flat['heads'].extend(len(flat['words'])+head for head in sent['heads'])
|
||||||
for field in ['words', 'tags', 'deps', 'entities', 'spaces']:
|
for field in ['words', 'tags', 'deps', 'morphology', 'entities', 'spaces']:
|
||||||
flat[field].extend(sent[field])
|
flat[field].extend(sent[field])
|
||||||
sent_starts.append(True)
|
sent_starts.append(True)
|
||||||
sent_starts.extend([False] * (len(sent['words'])-1))
|
sent_starts.extend([False] * (len(sent['words'])-1))
|
||||||
|
@ -238,22 +241,26 @@ def write_conllu(docs, file_):
|
||||||
def print_progress(itn, losses, ud_scores):
|
def print_progress(itn, losses, ud_scores):
|
||||||
fields = {
|
fields = {
|
||||||
'dep_loss': losses.get('parser', 0.0),
|
'dep_loss': losses.get('parser', 0.0),
|
||||||
|
'morph_loss': losses.get('morphologizer', 0.0),
|
||||||
'tag_loss': losses.get('tagger', 0.0),
|
'tag_loss': losses.get('tagger', 0.0),
|
||||||
'words': ud_scores['Words'].f1 * 100,
|
'words': ud_scores['Words'].f1 * 100,
|
||||||
'sents': ud_scores['Sentences'].f1 * 100,
|
'sents': ud_scores['Sentences'].f1 * 100,
|
||||||
'tags': ud_scores['XPOS'].f1 * 100,
|
'tags': ud_scores['XPOS'].f1 * 100,
|
||||||
'uas': ud_scores['UAS'].f1 * 100,
|
'uas': ud_scores['UAS'].f1 * 100,
|
||||||
'las': ud_scores['LAS'].f1 * 100,
|
'las': ud_scores['LAS'].f1 * 100,
|
||||||
|
'morph': ud_scores['Feats'].f1 * 100,
|
||||||
}
|
}
|
||||||
header = ['Epoch', 'Loss', 'LAS', 'UAS', 'TAG', 'SENT', 'WORD']
|
header = ['Epoch', 'P.Loss', 'M.Loss', 'LAS', 'UAS', 'TAG', 'MORPH', 'SENT', 'WORD']
|
||||||
if itn == 0:
|
if itn == 0:
|
||||||
print('\t'.join(header))
|
print('\t'.join(header))
|
||||||
tpl = '\t'.join((
|
tpl = '\t'.join((
|
||||||
'{:d}',
|
'{:d}',
|
||||||
'{dep_loss:.1f}',
|
'{dep_loss:.1f}',
|
||||||
|
'{morph_loss:.1f}',
|
||||||
'{las:.1f}',
|
'{las:.1f}',
|
||||||
'{uas:.1f}',
|
'{uas:.1f}',
|
||||||
'{tags:.1f}',
|
'{tags:.1f}',
|
||||||
|
'{morph:.1f}',
|
||||||
'{sents:.1f}',
|
'{sents:.1f}',
|
||||||
'{words:.1f}',
|
'{words:.1f}',
|
||||||
))
|
))
|
||||||
|
@ -275,7 +282,19 @@ def get_token_conllu(token, i):
|
||||||
head = 0
|
head = 0
|
||||||
else:
|
else:
|
||||||
head = i + (token.head.i - token.i) + 1
|
head = i + (token.head.i - token.i) + 1
|
||||||
fields = [str(i+1), token.text, token.lemma_, token.pos_, token.tag_, '_',
|
features = token.vocab.morphology.get(token.morph_key)
|
||||||
|
feat_str = []
|
||||||
|
replacements = {'one': '1', 'two': '2', 'three': '3'}
|
||||||
|
for feat in features:
|
||||||
|
if not feat.startswith('begin') and not feat.startswith('end'):
|
||||||
|
key, value = feat.split('_')
|
||||||
|
value = replacements.get(value, value)
|
||||||
|
feat_str.append('%s=%s' % (key, value.title()))
|
||||||
|
if not feat_str:
|
||||||
|
feat_str = '_'
|
||||||
|
else:
|
||||||
|
feat_str = '|'.join(feat_str)
|
||||||
|
fields = [str(i+1), token.text, token.lemma_, token.pos_, token.tag_, feat_str,
|
||||||
str(head), token.dep_.lower(), '_', '_']
|
str(head), token.dep_.lower(), '_', '_']
|
||||||
lines.append('\t'.join(fields))
|
lines.append('\t'.join(fields))
|
||||||
return '\n'.join(lines)
|
return '\n'.join(lines)
|
||||||
|
@ -305,6 +324,7 @@ def load_nlp(corpus, config, vectors=None):
|
||||||
|
|
||||||
def initialize_pipeline(nlp, docs, golds, config, device):
|
def initialize_pipeline(nlp, docs, golds, config, device):
|
||||||
nlp.add_pipe(nlp.create_pipe('tagger'))
|
nlp.add_pipe(nlp.create_pipe('tagger'))
|
||||||
|
nlp.add_pipe(nlp.create_pipe('morphologizer'))
|
||||||
nlp.add_pipe(nlp.create_pipe('parser'))
|
nlp.add_pipe(nlp.create_pipe('parser'))
|
||||||
if config.multitask_tag:
|
if config.multitask_tag:
|
||||||
nlp.parser.add_multitask_objective('tag')
|
nlp.parser.add_multitask_objective('tag')
|
||||||
|
@ -437,11 +457,11 @@ def main(ud_dir, parses_dir, corpus, config=None, limit=0, gpu_device=-1, vector
|
||||||
with nlp.use_params(optimizer.averages):
|
with nlp.use_params(optimizer.averages):
|
||||||
if use_oracle_segments:
|
if use_oracle_segments:
|
||||||
parsed_docs, scores = evaluate(nlp, paths.dev.conllu,
|
parsed_docs, scores = evaluate(nlp, paths.dev.conllu,
|
||||||
paths.dev.conllu, out_path)
|
paths.dev.conllu, out_path)
|
||||||
else:
|
else:
|
||||||
parsed_docs, scores = evaluate(nlp, paths.dev.text,
|
parsed_docs, scores = evaluate(nlp, paths.dev.text,
|
||||||
paths.dev.conllu, out_path)
|
paths.dev.conllu, out_path)
|
||||||
print_progress(i, losses, scores)
|
print_progress(i, losses, scores)
|
||||||
|
|
||||||
|
|
||||||
def _render_parses(i, to_render):
|
def _render_parses(i, to_render):
|
||||||
|
|
Loading…
Reference in New Issue
Block a user