| import time |
| import argparse |
|
|
| from transformers import AutoTokenizer |
|
|
| parser = argparse.ArgumentParser() |
| parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file") |
| parser.add_argument("--fname-tok", help="path to a text file to tokenize", required=True) |
| args = parser.parse_args() |
|
|
| dir_tokenizer = args.dir_tokenizer |
| fname_tok = args.fname_tok |
|
|
| tokenizer = AutoTokenizer.from_pretrained(dir_tokenizer) |
|
|
| print('tokenizing file: ', fname_tok) |
| fname_out = fname_tok + '.tok' |
| with open(fname_tok, 'r', encoding='utf-8') as f: |
| lines = f.readlines() |
| s = ''.join(lines) |
| t_start = time.time() |
| res = tokenizer.encode(s, add_special_tokens=False) |
| t_end = time.time() |
| print('\nmain : tokenized in', "{:.3f}".format(1000.0 * (t_end - t_start)), 'ms (py)') |
| with open(fname_out, 'w', encoding='utf-8') as f: |
| for x in res: |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| |
| f.write(str(x) + '\n') |
| print('len(res): ', len(res)) |
| print('len(lines): ', len(lines)) |
| print('results written to: ', fname_out) |
|
|