





from collections import namedtuple

import requests
from lxml import html  # type: ignore

A       :   Union[str, Any]					= namedtuple('''covid_data''', '''cases deaths recovered''')







def   __lowerCamelCase   (				__a  :str = "https://www.worldometers.info/coronavirus/"       )						->							covid_data:






		"""simple docstring"""

		A__     =  """//div[@class = \"maincounter-number\"]/span/text()"""
		return covid_data(*html.fromstring(requests.get(__a       ).content       ).xpath(__a       )       )


A       :   List[str]					= '''Total COVID-19 cases in the world: {}
Total deaths due to COVID-19 in the world: {}
Total COVID-19 patients recovered in the world: {}'''






print(fmt.format(*covid_stats()))










import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser







def   __lowerCamelCase   (				__a  :Optional[int]       )						->							str:






		"""simple docstring"""

		A__     =  {}
		A__     =  tokenizer(example["""content"""]       ,	truncation=__a       )["""input_ids"""]
		A__     =  len(example["""content"""]       ) / len(output["""input_ids"""]       )
		return output


A       :   Union[str, Any]					= HfArgumentParser(PretokenizationArguments)
A       :   str					= parser.parse_args()
if args.num_workers is None:
					A       :   Any					= multiprocessing.cpu_count()
A       :   int					= AutoTokenizer.from_pretrained(args.tokenizer_dir)

A       :   Optional[int]					= time.time()
A       :   int					= load_dataset(args.dataset_name, split='''train''')
print(F'''Dataset loaded in {time.time()-t_start:.2f}s''')

A       :   Optional[Any]					= time.time()
A       :   int					= ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        '''repo_name''',
        '''path''',
        '''copies''',
        '''size''',
        '''content''',
        '''license''',
        '''hash''',
        '''line_mean''',
        '''line_max''',
        '''alpha_frac''',
        '''autogenerated''',
    ],
)
print(F'''Dataset tokenized in {time.time()-t_start:.2f}s''')

A       :   Tuple					= time.time()
ds.push_to_hub(args.tokenized_data_repo)






print(F'''Data pushed to the hub in {time.time()-t_start:.2f}s''')



