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from typing import Optional, Dict, List, Union, Sequence
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from timeit import default_timer as timer
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import srsly
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from pydantic import BaseModel, FilePath
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import plac
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@ -520,6 +521,7 @@ def train_while_improving(
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raw_batches = util.minibatch(
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(nlp.make_doc(rt["text"]) for rt in raw_text), size=8
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)
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for step, batch in enumerate(train_data):
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dropout = next(dropouts)
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with nlp.select_pipes(enable=to_enable):
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