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Fix size limits in train_textcat example
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@ -43,7 +43,11 @@ def main(model=None, output_dir=None, n_iter=20, n_texts=2000, init_tok2vec=None
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# nlp.create_pipe works for built-ins that are registered with spaCy
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# nlp.create_pipe works for built-ins that are registered with spaCy
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if "textcat" not in nlp.pipe_names:
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if "textcat" not in nlp.pipe_names:
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textcat = nlp.create_pipe(
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textcat = nlp.create_pipe(
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"textcat", config={"architecture": "simple_cnn", "exclusive_classes": True}
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"textcat",
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config={
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"exclusive_classes": True,
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"architecture": "simple_cnn",
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}
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)
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)
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nlp.add_pipe(textcat, last=True)
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nlp.add_pipe(textcat, last=True)
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# otherwise, get it, so we can add labels to it
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# otherwise, get it, so we can add labels to it
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@ -56,7 +60,9 @@ def main(model=None, output_dir=None, n_iter=20, n_texts=2000, init_tok2vec=None
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# load the IMDB dataset
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# load the IMDB dataset
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print("Loading IMDB data...")
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print("Loading IMDB data...")
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(train_texts, train_cats), (dev_texts, dev_cats) = load_data(limit=n_texts)
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(train_texts, train_cats), (dev_texts, dev_cats) = load_data()
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train_texts = train_texts[:n_texts]
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train_cats = train_cats[:n_texts]
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print(
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print(
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"Using {} examples ({} training, {} evaluation)".format(
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"Using {} examples ({} training, {} evaluation)".format(
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n_texts, len(train_texts), len(dev_texts)
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n_texts, len(train_texts), len(dev_texts)
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