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@BrambleXu BrambleXu/
Last active Sep 11, 2018

What would you like to do?
load glove and show the progress, finally save to numpy file
import numpy as np
from tqdm import tqdm
def load_glove(file):
"""Loads GloVe vectors in numpy array.
file (str): a path to a glove file.
dict: a dict of numpy arrays.
embeddings_index = {}
with open(file, encoding='utf8') as f:
for i, line in tqdm(enumerate(f)):
values = line.split()
word = ''.join(values[:-300])
coefs = np.asarray(values[-300:], dtype='float32')
embeddings_index[word] = coefs
return embeddings_index
# EMBEDDING_PATH = '../embedding_weights/glove.840B.300d.txt'
EMBEDDING_PATH = 'glove.840B.300d.txt'
embeddings = load_glove(EMBEDDING_PATH)'glove_embeddings.npy', embeddings)
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