transformers/examples/distillation/scripts/token_counts.py
2019-08-28 04:00:03 +00:00

31 lines
1.1 KiB
Python

from collections import Counter
import argparse
import pickle
from utils import logger
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)")
parser.add_argument("--data_file", type=str, default="data/dump.bert-base-uncased.pickle",
help="The binarized dataset."
parser.add_argument("--token_counts_dump", type=str, default="data/token_counts.bert-base-uncased.pickle",
help="The dump file.")
parser.add_argument("--vocab_size", default=30522, type=int)
args = parser.parse_args()
logger.info(f'Loading data from {args.data_file}')
with open(args.data_file, 'rb') as fp:
data = pickle.load(fp)
logger.info('Counting occurences for MLM.')
counter = Counter()
for tk_ids in data:
counter.update(tk_ids)
counts = [0]*args.vocab_size
for k, v in counter.items():
counts[k] = v
logger.info(f'Dump to {args.token_counts_dump}')
with open(args.token_counts_dump, 'wb') as handle:
pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)