



'''simple docstring'''






from __future__ import annotations

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

UpperCamelCase__:       List[Any]							     =      {
    "A": ["B", "C"],
    "B": ["A", "D", "E"],
    "C": ["A", "F"],
    "D": ["B"],
    "E": ["B", "F"],
    "F": ["C", "E"],
}


def 			snake_case_					( _lowerCAmelCase  :						dict       ,				_lowerCAmelCase  :						str  )				->       list[str]:
							UpperCAmelCase			:	int										=		{start}
							UpperCAmelCase			:	List[Any]										=		[start]
							UpperCAmelCase			:	Tuple										=		Queue()
							queue.put(_lowerCAmelCase  )
							while not queue.empty():
														UpperCAmelCase			:	Union[str, Any]										=		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  :						dict       ,				_lowerCAmelCase  :						str  )				->       list[str]:
							UpperCAmelCase			:	Any										=		{start}
							UpperCAmelCase			:	List[str]										=		[start]
							UpperCAmelCase			:	int										=		deque([start]  )
							while queue:
														UpperCAmelCase			:	List[str]										=		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  :						str  )				->       None:
							UpperCAmelCase			:	List[Any]										=		f"""from __main__ import G, {name}"""
							UpperCAmelCase			:	Union[str, Any]										=		10000
							UpperCAmelCase			:	List[Any]										=		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_tokenizers_available, is_torch_available


UpperCamelCase__:       Tuple							     =      {
    "configuration_splinter": ["SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SplinterConfig"],
    "tokenization_splinter": ["SplinterTokenizer"],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:       Optional[Any]							     =      ["SplinterTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__:       Any							     =      [
						    "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SplinterForQuestionAnswering",
						    "SplinterForPreTraining",
						    "SplinterLayer",
						    "SplinterModel",
						    "SplinterPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
						from .tokenization_splinter import SplinterTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_splinter_fast import SplinterTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_splinter import (
												    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SplinterForPreTraining,
												    SplinterForQuestionAnswering,
												    SplinterLayer,
												    SplinterModel,
												    SplinterPreTrainedModel,
												)


else:
						import sys

						UpperCamelCase__:       Dict							     =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





