





from __future__ import annotations

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

_UpperCamelCase    =	{
    '''A''': ['''B''', '''C'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F'''],
    '''D''': ['''B'''],
    '''E''': ['''B''', '''F'''],
    '''F''': ['''C''', '''E'''],
}







def  lowerCAmelCase__(		lowercase    :      dict				,       lowercase    :      str			)	->      list[str]:
  __snake_case				:			Any            =    {start}
  __snake_case				:			Tuple            =    [start]
  __snake_case				:			Queue            =    Queue()
  queue.put(lowercase			)
  while not queue.empty():
    __snake_case				:			List[str]            =    queue.get()
    for w in graph[v]:
      if w not in explored:
        explored.add(lowercase			)
        result.append(lowercase			)
        queue.put(lowercase			)
  return result







def  lowerCAmelCase__(		lowercase    :      dict				,       lowercase    :      str			)	->      list[str]:
  __snake_case				:			int            =    {start}
  __snake_case				:			str            =    [start]
  __snake_case				:			Union[str, Any]            =    deque([start]			)
  while queue:
    __snake_case				:			Dict            =    queue.popleft()
    for child in graph[v]:
      if child not in visited:
        visited.add(lowercase			)
        result.append(lowercase			)
        queue.append(lowercase			)
  return result







def  lowerCAmelCase__(		lowercase    :      str			)	->      None:
  __snake_case				:			Dict            =    f"""from __main__ import G, {name}"""
  __snake_case				:			List[str]            =    1_0000
  __snake_case				:			List[str]            =    timeit(f"""{name}(G, 'A')"""				,       setup=lowercase				,       number=lowercase			)
  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








import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


_UpperCamelCase    =	logging.get_logger(__name__)




class 			_lowerCamelCase	(      a      ):



      """simple docstring"""






      def __init__(	self			,  *UpperCAmelCase			,  **UpperCAmelCase				)    ->				None:






        '''simple docstring'''






        warnings.warn(
            "The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
            " Please use MaskFormerImageProcessor instead."			,  UpperCAmelCase			,  )
        super().__init__(*UpperCAmelCase			,  **UpperCAmelCase				)

