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Fix train CLI
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@ -156,7 +156,7 @@ def train_cli(
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with init_tok2vec.open("rb") as file_:
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weights_data = file_.read()
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if num_workers and num_workers > 1:
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if num_workers and num_workers >= 1:
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from _ray_async_utils import distributed_setup_and_train
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distributed_setup_and_train(
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use_gpu,
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@ -172,6 +172,8 @@ def train_cli(
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)
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else:
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msg.info(f"Loading config from: {config_path}")
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if use_gpu >= 0:
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require_gpu(use_gpu)
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nlp, config = load_nlp_and_config(config_path)
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corpus = Corpus(train_path, dev_path, limit=config["training"]["limit"])
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