





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 						__A						(       lowerCamelCase_	,	lowerCamelCase_					):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE				:							Optional[int]						=	{start}
		SCREAMING_SNAKE_CASE				:							Union[str, Any]						=	[start]
		SCREAMING_SNAKE_CASE				:							Union[str, Any]						=	Queue()
		queue.put(lowerCamelCase_					)
		while not queue.empty():
				SCREAMING_SNAKE_CASE				:							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 						__A						(       lowerCamelCase_	,	lowerCamelCase_					):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE				:							Tuple						=	{start}
		SCREAMING_SNAKE_CASE				:							Optional[int]						=	[start]
		SCREAMING_SNAKE_CASE				:							Optional[Any]						=	deque([start]					)
		while queue:
				SCREAMING_SNAKE_CASE				:							int						=	queue.popleft()
				for child in graph[v]:
						if child not in visited:
								visited.add(lowerCamelCase_					)
								result.append(lowerCamelCase_					)
								queue.append(lowerCamelCase_					)
		return result



def 						__A						(       lowerCamelCase_					):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE				:							List[str]						=	f'''from __main__ import G, {name}'''
		SCREAMING_SNAKE_CASE				:							str						=	1_00_00
		SCREAMING_SNAKE_CASE				:							int						=	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 ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase         =   logging.get_logger(__name__)

__UpperCAmelCase         =   {
    """uw-madison/yoso-4096""": """https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json""",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}




class       UpperCamelCase__			(			lowercase_	):




					"""simple docstring"""
					SCREAMING_SNAKE_CASE__						=					'''yoso'''


					def __init__(		self							:	str     ,		lowerCamelCase_							:	Tuple=5_02_65     ,		lowerCamelCase_							:	int=7_68     ,		lowerCamelCase_							:	Optional[Any]=12     ,		lowerCamelCase_							:	int=12     ,		lowerCamelCase_							:	Optional[Any]=30_72     ,		lowerCamelCase_							:	str="gelu"     ,		lowerCamelCase_							:	Union[str, Any]=0.1     ,		lowerCamelCase_							:	int=0.1     ,		lowerCamelCase_							:	Optional[int]=40_96     ,		lowerCamelCase_							:	str=1     ,		lowerCamelCase_							:	str=0.02     ,		lowerCamelCase_							:	Dict=1e-12     ,		lowerCamelCase_							:	Tuple="absolute"     ,		lowerCamelCase_							:	Any=True     ,		lowerCamelCase_							:	Dict=9     ,		lowerCamelCase_							:	Any=64     ,		lowerCamelCase_							:	Union[str, Any]=None     ,		lowerCamelCase_							:	List[str]=True     ,		lowerCamelCase_							:	Dict=True     ,		lowerCamelCase_							:	int=1     ,		lowerCamelCase_							:	Tuple=0     ,		lowerCamelCase_							:	Dict=2     ,		**lowerCamelCase_							:	Tuple     ,		):

							'''simple docstring'''



							super().__init__(pad_token_id=lowerCamelCase_     ,		bos_token_id=lowerCamelCase_     ,		eos_token_id=lowerCamelCase_     ,		**lowerCamelCase_		)

							SCREAMING_SNAKE_CASE				:							int						=	vocab_size
							SCREAMING_SNAKE_CASE				:							List[Any]						=	max_position_embeddings
							SCREAMING_SNAKE_CASE				:							Tuple						=	hidden_size
							SCREAMING_SNAKE_CASE				:							Dict						=	num_hidden_layers
							SCREAMING_SNAKE_CASE				:							Any						=	num_attention_heads
							SCREAMING_SNAKE_CASE				:							int						=	intermediate_size
							SCREAMING_SNAKE_CASE				:							Optional[Any]						=	hidden_act
							SCREAMING_SNAKE_CASE				:							Optional[Any]						=	hidden_dropout_prob
							SCREAMING_SNAKE_CASE				:							List[Any]						=	attention_probs_dropout_prob
							SCREAMING_SNAKE_CASE				:							str						=	initializer_range
							SCREAMING_SNAKE_CASE				:							List[str]						=	type_vocab_size
							SCREAMING_SNAKE_CASE				:							List[str]						=	layer_norm_eps
							SCREAMING_SNAKE_CASE				:							Any						=	position_embedding_type
							SCREAMING_SNAKE_CASE				:							Optional[int]						=	use_expectation
							SCREAMING_SNAKE_CASE				:							int						=	hash_code_len
							SCREAMING_SNAKE_CASE				:							Union[str, Any]						=	num_hash
							SCREAMING_SNAKE_CASE				:							Optional[Any]						=	conv_window
							SCREAMING_SNAKE_CASE				:							Optional[Any]						=	use_fast_hash
							SCREAMING_SNAKE_CASE				:							Optional[int]						=	lsh_backward



