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Revert gold pre-processing to True
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@ -70,7 +70,7 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=20, n_sents=0,
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batch_sizes = util.compounding(util.env_opt('batch_from', 1),
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util.env_opt('batch_to', 64),
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util.env_opt('batch_compound', 1.001))
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gold_preproc = util.env_opt('gold_preproc', False)
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gold_preproc = util.env_opt('gold_preproc', True)
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noise_level = util.env_opt('noise_level', 0.0)
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if resume:
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