Read embeddings file in text format and convert to numpy

read_embeddings.py

import numpy as	np
import argparse

parser = argparse.ArgumentParser()
parser.add_argument('input', help='Single embedding file')
parser.add_argument('output', help='Output basename without extension')
args = parser.parse_args()

embeddings_file = args.output + '.npy'
vocabulary_file = args.output + '.txt'
words = []
vectors = []

with open(args.input, 'rb') as f:
    for line in f:
        fields = line.split()
        word = fields[0].decode('utf-8')
        vector = np.fromiter((float(x) for x in fields[1:]),
                             dtype=np.float)
        words.append(word)
        vectors.append(vector)

matrix = np.array(vectors)
np.save(embeddings_file, matrix)
text = '\n'.join(words)
with open(vocabulary_file, 'wb') as f:
    f.write(text.encode('utf-8'))

np.float not supported anymore in numpy 1.20 (https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations), can be exchanged with float or np.float64
otherwise useful script, thanks