from __future__ import annotations

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

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



def 			A__						(  lowercase_    :  dict			,   lowercase_    :  str	)     ->       list[str]:
   __lowerCamelCase								=				{start}
   __lowerCamelCase								=				[start]
   __lowerCamelCase								=				Queue()
   queue.put(lowercase_	)
   while not queue.empty():
      __lowerCamelCase								=				queue.get()
      for w in graph[v]:
         if w not in explored:
            explored.add(lowercase_	)
            result.append(lowercase_	)
            queue.put(lowercase_	)
   return result



def 			A__						(  lowercase_    :  dict			,   lowercase_    :  str	)     ->       list[str]:
   __lowerCamelCase								=				{start}
   __lowerCamelCase								=				[start]
   __lowerCamelCase								=				deque([start]	)
   while queue:
      __lowerCamelCase								=				queue.popleft()
      for child in graph[v]:
         if child not in visited:
            visited.add(lowercase_	)
            result.append(lowercase_	)
            queue.append(lowercase_	)
   return result



def 			A__						(  lowercase_    :  str	)     ->       None:
   __lowerCamelCase								=				F'''from __main__ import G, {name}'''
   __lowerCamelCase								=				10000
   __lowerCamelCase								=				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







"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_SCREAMING_SNAKE_CASE  :		List[Any]        =      {
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE  :		Optional[Any]        =      ['''DeformableDetrFeatureExtractor''']
     _SCREAMING_SNAKE_CASE  :		List[str]        =      ['''DeformableDetrImageProcessor''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE  :		Union[str, Any]        =      [
         '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''DeformableDetrForObjectDetection''',
         '''DeformableDetrModel''',
         '''DeformableDetrPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
          from .image_processing_deformable_detr import DeformableDetrImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_deformable_detr import (
              DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DeformableDetrForObjectDetection,
              DeformableDetrModel,
              DeformableDetrPreTrainedModel,
          )

else:
     import sys

     _SCREAMING_SNAKE_CASE  :		Tuple        =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






