




'''simple docstring'''





from __future__ import annotations

from collections import deque
from queue import Queue
from timeit import timeit

__SCREAMING_SNAKE_CASE    :   int       ={
    """A""": ["""B""", """C"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E"""],
}

def 			lowerCAmelCase_			(  lowerCamelCase:       dict     ,				lowerCamelCase:       str						)					->			list[str]:


      '''simple docstring'''




      lowerCamelCase__        =				{start}
      lowerCamelCase__        =				[start]
      lowerCamelCase__        =				Queue()
      queue.put(lowerCamelCase						)
      while not queue.empty():
            lowerCamelCase__        =				queue.get()
            for w in graph[v]:
                  if w not in explored:
                        explored.add(lowerCamelCase						)
                        result.append(lowerCamelCase						)
                        queue.put(lowerCamelCase						)
      return result

def 			lowerCAmelCase_			(  lowerCamelCase:       dict     ,				lowerCamelCase:       str						)					->			list[str]:


      '''simple docstring'''




      lowerCamelCase__        =				{start}
      lowerCamelCase__        =				[start]
      lowerCamelCase__        =				deque([start]						)
      while queue:
            lowerCamelCase__        =				queue.popleft()
            for child in graph[v]:
                  if child not in visited:
                        visited.add(lowerCamelCase						)
                        result.append(lowerCamelCase						)
                        queue.append(lowerCamelCase						)
      return result

def 			lowerCAmelCase_			(  lowerCamelCase:       str						)					->			None:


      '''simple docstring'''




      lowerCamelCase__        =				f"""from __main__ import G, {name}"""
      lowerCamelCase__        =				1_00_00
      lowerCamelCase__        =				timeit(f"""{name}(G, 'A')"""     ,				setup=lowerCamelCase     ,				number=lowerCamelCase						)
      print(f"""{name:<35} finished {number} runs in {res:.5f} seconds"""						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      benchmark_function("""breadth_first_search""")
      benchmark_function("""breadth_first_search_with_deque""")
      # breadth_first_search                finished 10000 runs in 0.20999 seconds
      # breadth_first_search_with_deque     finished 10000 runs in 0.01421 seconds





from ..utils import DummyObject, requires_backends






class 			A			(		metaclass=_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:	Optional[Any]     =["torch", "transformers", "invisible_watermark"]




     def __init__(    self  :   Dict	,  *A__  :   Optional[int]	,  **A__  :   Dict			)				->       Union[str, Any]:
           requires_backends(self	,  ['torch', 'transformers', 'invisible_watermark']			)




     @classmethod
     def  __snake_case   (    cls  :   Optional[int]	,  *A__  :   Dict	,  **A__  :   List[str]			)				->       Union[str, Any]:
           requires_backends(cls	,  ['torch', 'transformers', 'invisible_watermark']			)




     @classmethod
     def  __snake_case   (    cls  :   Optional[Any]	,  *A__  :   Dict	,  **A__  :   List[Any]			)				->       Dict:
           requires_backends(cls	,  ['torch', 'transformers', 'invisible_watermark']			)






class 			A			(		metaclass=_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:	Dict     =["torch", "transformers", "invisible_watermark"]




     def __init__(    self  :   List[str]	,  *A__  :   str	,  **A__  :   int			)				->       List[Any]:
           requires_backends(self	,  ['torch', 'transformers', 'invisible_watermark']			)




     @classmethod
     def  __snake_case   (    cls  :   str	,  *A__  :   Any	,  **A__  :   Dict			)				->       Optional[Any]:
           requires_backends(cls	,  ['torch', 'transformers', 'invisible_watermark']			)




     @classmethod
     def  __snake_case   (    cls  :   List[str]	,  *A__  :   Optional[Any]	,  **A__  :   int			)				->       Dict:
           requires_backends(cls	,  ['torch', 'transformers', 'invisible_watermark']			)