
from argparse import ArgumentParser

from . import BaseTransformersCLICommand


def     __lowerCAmelCase			(			a__  )       ->  Union[str, Any]:
				return DownloadCommand(args.model						,    args.cache_dir						,    args.force						,    args.trust_remote_code  )







class 			__A( a			):




				@staticmethod
				def 				SCREAMING_SNAKE_CASE_		(     _snake_case				)    ->      int:


								'''simple docstring'''




								__a										=    parser.add_parser('''download'''				)
								download_parser.add_argument(
								    '''--cache-dir'''		,     type=_snake_case		,     default=_snake_case		,     help='''Path to location to store the models'''				)
								download_parser.add_argument(
								    '''--force'''		,     action='''store_true'''		,     help='''Force the model to be download even if already in cache-dir'''				)
								download_parser.add_argument(
								    '''--trust-remote-code'''		,     action='''store_true'''		,     help='''Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'''		,     )
								download_parser.add_argument('''model'''		,     type=_snake_case		,     help='''Name of the model to download'''				)
								download_parser.set_defaults(func=_snake_case				)




				def __init__(     self		,     _snake_case		,     _snake_case		,     _snake_case		,     _snake_case				)    ->      Dict:


								'''simple docstring'''




								__a										=    model
								__a										=    cache
								__a										=    force
								__a										=    trust_remote_code




				def 				SCREAMING_SNAKE_CASE_		(     self				)    ->      List[str]:


								'''simple docstring'''




								from ..models.auto import AutoModel, AutoTokenizer

								AutoModel.from_pretrained(
								    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code				)
								AutoTokenizer.from_pretrained(
								    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code				)






import random




def 		lowerCAmelCase_    (  __UpperCAmelCase:			list		,   __UpperCAmelCase:			Optional[int]      )      ->	tuple:
    UpperCamelCase__   ,UpperCamelCase__   ,UpperCamelCase__							:				List[Any]          =      [], [], []
    for element in data:
        if element < pivot:
            less.append(__UpperCAmelCase      )
        elif element > pivot:
            greater.append(__UpperCAmelCase      )
        else:
            equal.append(__UpperCAmelCase      )
    return less, equal, greater





def 		lowerCAmelCase_    (  __UpperCAmelCase:			list		,   __UpperCAmelCase:			int      )      ->	List[str]:
    # index = len(items) // 2 when trying to find the median
    #   (value of index when items is sorted)

    # invalid input
    if index >= len(__UpperCAmelCase      ) or index < 0:
        return None

    UpperCamelCase__							:				List[str]          =      items[random.randint(0		,   len(__UpperCAmelCase      ) - 1      )]
    UpperCamelCase__							:				List[Any]          =      0
    UpperCamelCase__   ,UpperCamelCase__   ,UpperCamelCase__							:				int          =      _partition(__UpperCAmelCase		,   __UpperCAmelCase      )
    UpperCamelCase__							:				Union[str, Any]          =      len(__UpperCAmelCase      )
    UpperCamelCase__							:				Dict          =      len(__UpperCAmelCase      )

    # index is the pivot
    if m <= index < m + count:
        return pivot
    # must be in smaller
    elif m > index:
        return quick_select(__UpperCAmelCase		,   __UpperCAmelCase      )
    # must be in larger
    else:
        return quick_select(__UpperCAmelCase		,   index - (m + count)      )

