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	Remove vector pruning arg from train CLI
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				|  | @ -32,7 +32,6 @@ numpy.random.seed(0) | |||
|     n_sents=("number of sentences", "option", "ns", int), | ||||
|     use_gpu=("Use GPU", "option", "g", int), | ||||
|     vectors=("Model to load vectors from", "option", "v"), | ||||
|     vectors_limit=("Truncate to N vectors (requires -v)", "option", None, int), | ||||
|     no_tagger=("Don't train tagger", "flag", "T", bool), | ||||
|     no_parser=("Don't train parser", "flag", "P", bool), | ||||
|     no_entities=("Don't train NER", "flag", "N", bool), | ||||
|  | @ -41,7 +40,7 @@ numpy.random.seed(0) | |||
|     meta_path=("Optional path to meta.json. All relevant properties will be " | ||||
|                "overwritten.", "option", "m", Path)) | ||||
| def train(cmd, lang, output_dir, train_data, dev_data, n_iter=30, n_sents=0, | ||||
|           use_gpu=-1, vectors=None, vectors_limit=None, no_tagger=False, | ||||
|           use_gpu=-1, vectors=None, no_tagger=False, | ||||
|           no_parser=False, no_entities=False, gold_preproc=False, | ||||
|           version="0.0.0", meta_path=None): | ||||
|     """ | ||||
|  | @ -95,8 +94,6 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=30, n_sents=0, | |||
|     nlp.meta.update(meta) | ||||
|     if vectors: | ||||
|         util.load_model(vectors, vocab=nlp.vocab) | ||||
|         if vectors_limit is not None: | ||||
|             nlp.vocab.prune_vectors(vectors_limit) | ||||
|     for name in pipeline: | ||||
|         nlp.add_pipe(nlp.create_pipe(name), name=name) | ||||
|     optimizer = nlp.begin_training(lambda: corpus.train_tuples, device=use_gpu) | ||||
|  |  | |||
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