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Improve train_ud script
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@ -18,6 +18,7 @@ from spacy.pipeline import DependencyParser
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from spacy.syntax.parser import get_templates
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from spacy.syntax.arc_eager import ArcEager
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from spacy.scorer import Scorer
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from spacy.language_data.tag_map import TAG_MAP as DEFAULT_TAG_MAP
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import spacy.attrs
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import io
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@ -61,9 +62,12 @@ def score_model(vocab, tagger, parser, gold_docs, verbose=False):
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return scorer
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def main(train_loc, dev_loc, model_dir, tag_map_loc):
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def main(train_loc, dev_loc, model_dir, tag_map_loc=None):
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if tag_map_loc:
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with open(tag_map_loc) as file_:
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tag_map = json.loads(file_.read())
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else:
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tag_map = DEFAULT_TAG_MAP
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train_sents = list(read_conllx(train_loc))
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train_sents = PseudoProjectivity.preprocess_training_data(train_sents)
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@ -73,9 +77,10 @@ def main(train_loc, dev_loc, model_dir, tag_map_loc):
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model_dir = pathlib.Path(model_dir)
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if not (model_dir / 'deps').exists():
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(model_dir / 'deps').mkdir()
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with (model_dir / 'deps' / 'config.json').open('w') as file_:
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json.dump({'pseudoprojective': True, 'labels': actions, 'features': features}, file_)
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with (model_dir / 'deps' / 'config.json').open('wb') as file_:
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file_.write(
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json.dumps(
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{'pseudoprojective': True, 'labels': actions, 'features': features}).encode('utf8'))
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vocab = Vocab(lex_attr_getters=Language.Defaults.lex_attr_getters, tag_map=tag_map)
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# Populate vocab
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for _, doc_sents in train_sents:
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@ -86,6 +91,7 @@ def main(train_loc, dev_loc, model_dir, tag_map_loc):
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_ = vocab[dep]
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for tag in tags:
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_ = vocab[tag]
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if tag_map:
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for tag in tags:
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assert tag in tag_map, repr(tag)
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tagger = Tagger(vocab, tag_map=tag_map)
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