'''simple docstring'''


from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments


def  _lowerCamelCase   (				):



     """simple docstring"""





     UpperCAmelCase_							:       Tuple       =				HfArgumentParser(lowerCamelCase_       )
     UpperCAmelCase_							:       int       =				parser.parse_args_into_dataclasses()[0]
     UpperCAmelCase_							:       str       =				TensorFlowBenchmark(args=lowerCamelCase_       )
     try:
          UpperCAmelCase_							:       Dict       =				parser.parse_args_into_dataclasses()[0]
     except ValueError as e:
          UpperCAmelCase_							:       Any       =				'Arg --no_{0} is no longer used, please use --no-{0} instead.'
          UpperCAmelCase_							:       Dict       =				' '.join(str(lowerCamelCase_       ).split(' '       )[:-1]       )
          UpperCAmelCase_							:       Dict       =				''
          UpperCAmelCase_							:       Optional[Any]       =				eval(str(lowerCamelCase_       ).split(' '       )[-1]       )
          UpperCAmelCase_							:       Optional[Any]       =				[]
          for arg in depreciated_args:
               # arg[2:] removes '--'
               if arg[2:] in TensorFlowBenchmark.deprecated_args:
                    # arg[5:] removes '--no_'
                    full_error_msg += arg_error_msg.format(arg[5:]       )
               else:
                    wrong_args.append(lowerCamelCase_       )
          if len(lowerCamelCase_       ) > 0:
               UpperCAmelCase_							:       List[Any]       =				full_error_msg + begin_error_msg + str(lowerCamelCase_       )
          raise ValueError(lowerCamelCase_       )
     benchmark.run()


if __name__ == "__main__":
 main()







'''simple docstring'''


from __future__ import annotations

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






@dataclass
class 					__SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  lowerCamelCase_		:int
  lowerCamelCase_		:int







class 					__SCREAMING_SNAKE_CASE						:







  '''simple docstring'''






  def __init__(			self				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       list[list[Edge]]       =				[[] for _ in range(snake_case_						)]
       UpperCAmelCase_							:       Any       =				size


  def __getitem__(			self				,		snake_case_						):




       '''simple docstring'''

       return iter(self._graph[vertex]						)


  @property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       return self._size


  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_				,		snake_case_						):




       '''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(snake_case_				,		snake_case_						)						)






  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[int]       =				deque([start_vertex]						)
       UpperCAmelCase_							:       list[int | None]       =				[None] * self.size
       UpperCAmelCase_							:       str       =				0

       while queue:
            UpperCAmelCase_							:       Optional[int]       =				queue.popleft()
            UpperCAmelCase_							:       List[str]       =				distances[current_vertex]
            if current_distance is None:
                 continue

            for edge in self[current_vertex]:
                 UpperCAmelCase_							:       Union[str, Any]       =				current_distance + edge.weight
                 UpperCAmelCase_							:       Union[str, Any]       =				distances[edge.destination_vertex]
                 if (
                     isinstance(snake_case_				,		snake_case_						)
                     and new_distance >= dest_vertex_distance
                 ):
                      continue
                 UpperCAmelCase_							:       Optional[Any]       =				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()






