from argparse import ArgumentParser

from . import BaseTransformersCLICommand





def 						__lowerCamelCase				(UpperCAmelCase__  :				Optional[int]	):
					return DownloadCommand(args.model   ,			args.cache_dir   ,			args.force   ,			args.trust_remote_code	)


class     lowercase     (  _a  ):




							@staticmethod
							def 						__snake_case(    _UpperCamelCase :       ArgumentParser   )       ->					Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							parser.add_parser("download"   )
												download_parser.add_argument(
												    "--cache-dir"						,				type=lowerCAmelCase_						,				default=lowerCAmelCase_						,				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=lowerCAmelCase_						,				help="Name of the model to download"   )
												download_parser.set_defaults(func=lowerCAmelCase_   )




							def __init__(    self :       Any						,				_UpperCamelCase :       str						,				_UpperCamelCase :       str						,				_UpperCamelCase :       bool						,				_UpperCamelCase :       bool   )       ->					Tuple:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =							model
												SCREAMING_SNAKE_CASE           =							cache
												SCREAMING_SNAKE_CASE           =							force
												SCREAMING_SNAKE_CASE           =							trust_remote_code





							def 						__snake_case(    self :       int   )       ->					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   )










'''simple docstring'''


from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass

@dataclass
class      A       :
							lowercase_							     =							42
							lowercase_							     =							42



class      A       :







							def __init__(    self			:    Optional[Any]				,     lowerCAmelCase_			:    int   )     ->				str:


														"""simple docstring"""


														_a      	=							[[] for _ in range(lowerCAmelCase_   )]
														_a      	=							size







							def __getitem__(    self			:    Any				,     lowerCAmelCase_			:    int   )     ->				Iterator[Edge]:


														"""simple docstring"""


														return iter(self._graph[vertex]   )







							@property
							def   __lowerCAmelCase     (    self			:    str   )     ->				Tuple:


														"""simple docstring"""


														return self._size







							def   __lowerCAmelCase     (    self			:    Union[str, Any]				,     lowerCAmelCase_			:    int				,     lowerCAmelCase_			:    int				,     lowerCAmelCase_			:    int   )     ->				Dict:


														"""simple docstring"""


														if weight not in (0, 1):
																					raise ValueError('''Edge weight must be either 0 or 1.'''   )

														if to_vertex < 0 or to_vertex >= self.size:
																					raise ValueError('''Vertex indexes must be in [0; size).'''   )

														self._graph[from_vertex].append(Edge(lowerCAmelCase_				,     lowerCAmelCase_   )   )







							def   __lowerCAmelCase     (    self			:    Tuple				,     lowerCAmelCase_			:    int				,     lowerCAmelCase_			:    int   )     ->				int | None:


														"""simple docstring"""


														_a      	=							deque([start_vertex]   )
														_a      	=							[None] * self.size
														_a      	=							0

														while queue:
																					_a      	=							queue.popleft()
																					_a      	=							distances[current_vertex]
																					if current_distance is None:
																												continue

																					for edge in self[current_vertex]:
																												_a      	=							current_distance + edge.weight
																												_a      	=							distances[edge.destination_vertex]
																												if (
																												    isinstance(lowerCAmelCase_				,     lowerCAmelCase_   )
																												    and new_distance >= dest_vertex_distance
																												):
																																			continue
																												_a      	=							new_distance
																												if edge.weight == 0:
																																			queue.appendleft(edge.destination_vertex   )
																												else:
																																			queue.append(edge.destination_vertex   )

														if distances[finish_vertex] is None:
																					raise ValueError('''No path from start_vertex to finish_vertex.'''   )

														return distances[finish_vertex]


if __name__ == "__main__":
				import doctest

				doctest.testmod()

