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libmultilabel/nn/data_utils.py

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@@ -389,9 +389,9 @@ def load_or_build_label(datasets, label_file=None, include_test_labels=False):
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def get_embedding_weights_from_file(word_dict, embed_file, silent=False, cache_dir=None):
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"""Obtain the word embeddings from file. If the word exists in the embedding file,
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"""Obtain the word embeddings from file. If the word exists in the embedding file,
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load the pretrained word embedding. Otherwise, assign a zero vector to that word.
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If the given `embed_file` is the name of a pretrained GloVe embedding, the function
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If the given `embed_file` is the name of a pretrained GloVe embedding, the function
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will first download the corresponding file.
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Args:

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