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Don't collate model unless training succeeds

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This commit is contained in:
Matthew Honnibal 2018-06-25 16:36:42 +02:00
parent 24dfbb8a28
commit c4698f5712
1 changed files with 9 additions and 8 deletions
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17
spacy/cli/train.py
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@ -187,14 +187,15 @@ def train(lang, output_dir, train_data, dev_data, n_iter=30, n_sents=0,
with nlp.use_params(optimizer.averages): with nlp.use_params(optimizer.averages):
final_model_path = output_path / 'model-final' final_model_path = output_path / 'model-final'
nlp.to_disk(final_model_path) nlp.to_disk(final_model_path)
components = [] components = []
if not no_parser: if not no_parser:
components.append('parser') components.append('parser')
if not no_tagger: if not no_tagger:
components.append('tagger') components.append('tagger')
if not no_entities: if not no_entities:
components.append('ner') components.append('ner')
_collate_best_model(meta, output_path, components) _collate_best_model(meta, output_path, components)
def _collate_best_model(meta, output_path, components): def _collate_best_model(meta, output_path, components):
bests = {} bests = {}