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Pass gold_preproc setting into corpus

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This commit is contained in:
Matthew Honnibal 2020-06-22 17:48:50 +02:00
parent 03b3da26be
commit b5cd310543
1 changed files with 10 additions and 3 deletions
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13
spacy/cli/train.py
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@ -213,7 +213,11 @@ def train(
nlp.resume_training() nlp.resume_training()
else: else:
msg.info(f"Initializing the nlp pipeline: {nlp.pipe_names}") msg.info(f"Initializing the nlp pipeline: {nlp.pipe_names}")
train_examples = list(corpus.train_dataset(nlp, shuffle=False)) train_examples = list(corpus.train_dataset(
nlp,
shuffle=False,
gold_preproc=training["gold_preproc"]
))
nlp.begin_training(lambda: train_examples) nlp.begin_training(lambda: train_examples)
# Update tag map with provided mapping # Update tag map with provided mapping
@ -305,10 +309,13 @@ def train(
def create_train_batches(nlp, corpus, cfg): def create_train_batches(nlp, corpus, cfg):
epochs_todo = cfg.get("max_epochs", 0) epochs_todo = cfg.get("max_epochs", 0)
while True: while True:
train_examples = list(corpus.train_dataset(nlp)) train_examples = list(corpus.train_dataset(
nlp,
shuffle=True,
gold_preproc=cfg["gold_preproc"]
))
if len(train_examples) == 0: if len(train_examples) == 0:
raise ValueError(Errors.E988) raise ValueError(Errors.E988)
random.shuffle(train_examples)
batches = util.minibatch_by_words( batches = util.minibatch_by_words(
train_examples, train_examples,
size=cfg["batch_size"], size=cfg["batch_size"],