'''simple docstring'''





import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp






def SCREAMING_SNAKE_CASE__  (				)   ->				int:







     """simple docstring"""
     a					:							Tuple							= ArgumentParser(
         description=(
             'PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'
         )  )

     # Optional arguments for the launch helper
     parser.add_argument('--num_cores'				,	type=_lowercase				,	default=1				,	help='Number of TPU cores to use (1 or 8).'  )

     # positional
     parser.add_argument(
         'training_script'				,	type=_lowercase				,	help=(
             'The full path to the single TPU training '
             'program/script to be launched in parallel, '
             'followed by all the arguments for the '
             'training script'
         )				,	)

     # rest from the training program
     parser.add_argument('training_script_args'				,	nargs=_lowercase  )

     return parser.parse_args()






def SCREAMING_SNAKE_CASE__  (				)   ->				str:







     """simple docstring"""
     a					:							List[str]							= parse_args()

     # Import training_script as a module.
     a					:							Optional[Any]							= Path(args.training_script  )
     sys.path.append(str(script_fpath.parent.resolve()  )  )
     a					:							Union[str, Any]							= script_fpath.stem
     a					:							Tuple							= importlib.import_module(_lowercase  )

     # Patch sys.argv
     a					:							str							= [args.training_script] + args.training_script_args + ['--tpu_num_cores', str(args.num_cores  )]

     xmp.spawn(mod._mp_fn				,	args=()				,	nprocs=args.num_cores  )


if __name__ == "__main__":
      main()






'''simple docstring'''

import bsa
import requests







def     __UpperCamelCase					(				_lowercase       )			->      dict[str, str]:
	return {
	    "name": soup.ha.a.text,
	    "genre": soup.find('span',					class_='genre'       ).text.strip(),
	    "rating": soup.strong.text,
	    "page_link": f'''https://www.imdb.com{soup.a.get("href"       )}''',
	}







def     __UpperCamelCase					(				_lowercase = 5       )			->      tuple:
	_lowercase       :							List[Any]  	=		int(float(_lowercase       )       )
	if num_movies < 1:
		return ()
	_lowercase       :							Any  	=		(
	    'https://www.imdb.com/search/title?title_type='
	    f'''feature&sort=num_votes,desc&count={num_movies}'''
	)
	_lowercase       :							Tuple  	=		bsa.BeautifulSoup(requests.get(_lowercase       ).content,					'html.parser'       )
	return tuple(
	    get_movie_data_from_soup(_lowercase       )
	    for movie in source.find_all('div',					class_='lister-item mode-advanced'       )       )


if __name__ == "__main__":
		import json

		_A					:     Optional[int]      =int(input('''How many movies would you like to see? '''))
		print(
		    ''', '''.join(
		        json.dumps(movie, indent=4) for movie in get_imdb_top_movies(num_movies)
		    )
		)
