load glove and show the progress, finally save to numpy file

glove2npy.py

import numpy as np
from tqdm import tqdm


def load_glove(file):
    """Loads GloVe vectors in numpy array.
    Args:
        file (str): a path to a glove file.
    Return:
        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)
 
np.save('glove_embeddings.npy', embeddings)