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fix merge conflict
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@ -13,11 +13,7 @@ from thinc.api import Model, use_pytorch_for_gpu_memory
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import random
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import random
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from ..gold import GoldCorpus
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from ..gold import GoldCorpus
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<<<<<<< HEAD
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from ..gold import Example
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=======
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from ..lookups import Lookups
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from ..lookups import Lookups
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>>>>>>> origin/develop
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from .. import util
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from .. import util
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from ..errors import Errors
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from ..errors import Errors
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from ..ml import models # don't remove - required to load the built-in architectures
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from ..ml import models # don't remove - required to load the built-in architectures
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@ -374,27 +370,17 @@ def train(
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def create_train_batches(nlp, corpus, cfg):
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def create_train_batches(nlp, corpus, cfg):
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epochs_todo = cfg.get("max_epochs", 0)
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epochs_todo = cfg.get("max_epochs", 0)
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while True:
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while True:
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<<<<<<< HEAD
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train_examples = list(corpus.train_dataset(
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nlp,
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noise_level=0.0,
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orth_variant_level=cfg["orth_variant_level"],
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gold_preproc=cfg["gold_preproc"],
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max_length=cfg["max_length"],
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ignore_misaligned=True
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))
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=======
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train_examples = list(
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train_examples = list(
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corpus.train_dataset(
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corpus.train_dataset(
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nlp,
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nlp,
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noise_level=0.0, # I think this is deprecated?
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noise_level=cfg["noise_level"], # I think this is deprecated?
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orth_variant_level=cfg["orth_variant_level"],
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orth_variant_level=cfg["orth_variant_level"],
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gold_preproc=cfg["gold_preproc"],
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gold_preproc=cfg["gold_preproc"],
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max_length=cfg["max_length"],
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max_length=cfg["max_length"],
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ignore_misaligned=True,
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ignore_misaligned=True,
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)
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)
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)
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)
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>>>>>>> origin/develop
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if len(train_examples) == 0:
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if len(train_examples) == 0:
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raise ValueError(Errors.E988)
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raise ValueError(Errors.E988)
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random.shuffle(train_examples)
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random.shuffle(train_examples)
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