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Fixed vocabulary in the entity linker training example (#5676) 

* entity linker training example: model loading changed according to issue 5668 (https://github.com/explosion/spaCy/issues/5668) + vocab_path is a required argument

* contributor agreement
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Matthias Hertel 2020-07-03 10:24:02 +02:00 committed by GitHub
parent a77c4c3465
commit 2fb9bd795d
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1 changed files with 3 additions and 3 deletions
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6
examples/training/train_entity_linker.py
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@ -60,12 +60,12 @@ TRAIN_DATA = sample_train_data()
output_dir=("Optional output directory", "option", "o", Path),
n_iter=("Number of training iterations", "option", "n", int),
)
def main(kb_path, vocab_path=None, output_dir=None, n_iter=50):
def main(kb_path, vocab_path, output_dir=None, n_iter=50):
"""Create a blank model with the specified vocab, set up the pipeline and train the entity linker.
The `vocab` should be the one used during creation of the KB."""
vocab = Vocab().from_disk(vocab_path)
# create blank English model with correct vocab
nlp = spacy.blank("en", vocab=vocab)
nlp = spacy.blank("en")
nlp.vocab.from_disk(vocab_path)
nlp.vocab.vectors.name = "spacy_pretrained_vectors"
print("Created blank 'en' model with vocab from '%s'" % vocab_path)