'''simple docstring'''




from __future__ import annotations

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

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



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



def 						__snake_case (       lowerCAmelCase      ,  lowerCAmelCase			):
 __UpperCAmelCase         =					{start}
 __UpperCAmelCase         =					[start]
 __UpperCAmelCase         =					deque([start]			)
 while queue:
  __UpperCAmelCase         =					queue.popleft()
  for child in graph[v]:
   if child not in visited:
    visited.add(lowerCAmelCase			)
    result.append(lowerCAmelCase			)
    queue.append(lowerCAmelCase			)
 return result



def 						__snake_case (       lowerCAmelCase			):
 __UpperCAmelCase         =					F"""from __main__ import G, {name}"""
 __UpperCAmelCase         =					1_0000
 __UpperCAmelCase         =					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




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_UpperCamelCase				:		int       			=		{
    'configuration_align': [
        'ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AlignConfig',
        'AlignTextConfig',
        'AlignVisionConfig',
    ],
    'processing_align': ['AlignProcessor'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		Optional[Any]       			=		[
         'ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST',
         'AlignModel',
         'AlignPreTrainedModel',
         'AlignTextModel',
         'AlignVisionModel',
     ]

if TYPE_CHECKING:
     from .configuration_align import (
         ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
         AlignConfig,
         AlignTextConfig,
         AlignVisionConfig,
     )
     from .processing_align import AlignProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_align import (
              ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
              AlignModel,
              AlignPreTrainedModel,
              AlignTextModel,
              AlignVisionModel,
          )

else:
     import sys

     _UpperCamelCase				:		str       			=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



