
'''simple docstring'''







from queue import PriorityQueue
from typing import Any

import numpy as np



def 			_a		(	_SCREAMING_SNAKE_CASE		:   dict	,			_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   set	,			_SCREAMING_SNAKE_CASE		:   set	,			_SCREAMING_SNAKE_CASE		:   dict	,			_SCREAMING_SNAKE_CASE		:   dict	,			_SCREAMING_SNAKE_CASE		:   PriorityQueue	,			_SCREAMING_SNAKE_CASE		:   dict	,			_SCREAMING_SNAKE_CASE		:   float | int	,			):





						for nxt, d in graph[v]:
												if nxt in visited_forward:
																		continue
												_SCREAMING_SNAKE_CASE				= cst_fwd.get(_lowerCamelCase	,			np.inf  )
												_SCREAMING_SNAKE_CASE				= cst_fwd[v] + d
												if new_cost_f < old_cost_f:
																		queue.put((new_cost_f, nxt)  )
																		_SCREAMING_SNAKE_CASE				= new_cost_f
																		_SCREAMING_SNAKE_CASE				= v
												if nxt in visited_backward:
																		if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
																								_SCREAMING_SNAKE_CASE				= cst_fwd[v] + d + cst_bwd[nxt]
						return shortest_distance



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   dict	,			_SCREAMING_SNAKE_CASE		:   dict  ):
						_SCREAMING_SNAKE_CASE				= -1

						_SCREAMING_SNAKE_CASE				= set()
						_SCREAMING_SNAKE_CASE				= set()
						_SCREAMING_SNAKE_CASE				= {source: 0}
						_SCREAMING_SNAKE_CASE				= {destination: 0}
						_SCREAMING_SNAKE_CASE				= {source: None}
						_SCREAMING_SNAKE_CASE				= {destination: None}
						_SCREAMING_SNAKE_CASE				= PriorityQueue()
						_SCREAMING_SNAKE_CASE				= PriorityQueue()

						_SCREAMING_SNAKE_CASE				= np.inf

						queue_forward.put((0, source)  )
						queue_backward.put((0, destination)  )

						if source == destination:
												return 0

						while not queue_forward.empty() and not queue_backward.empty():
												_SCREAMING_SNAKE_CASE				= queue_forward.get()
												visited_forward.add(_lowerCamelCase  )

												_SCREAMING_SNAKE_CASE				= queue_backward.get()
												visited_backward.add(_lowerCamelCase  )

												_SCREAMING_SNAKE_CASE				= pass_and_relaxation(
												    _lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			)

												_SCREAMING_SNAKE_CASE				= pass_and_relaxation(
												    _lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			_lowerCamelCase	,			)

												if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
																		break

						if shortest_distance != np.inf:
												_SCREAMING_SNAKE_CASE				= shortest_distance
						return shortest_path_distance


_snake_case				:   Union[str, Any]     =				{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
_snake_case				:   List[Any]     =				{
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
						import doctest

						doctest.testmod()

'''simple docstring'''







from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class 			lowerCAmelCase (				__UpperCAmelCase			):
		a							:					Dict       =					DistilBertTokenizer
		a							:					Tuple       =					DistilBertTokenizerFast
		a							:					List[str]       =					True




		@slow
		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= DistilBertTokenizer.from_pretrained("distilbert-base-uncased"      )

								_SCREAMING_SNAKE_CASE				= tokenizer.encode("sequence builders"					,						add_special_tokens=UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= tokenizer.encode("multi-sequence build"					,						add_special_tokens=UpperCamelCase      )

								_SCREAMING_SNAKE_CASE				= tokenizer.build_inputs_with_special_tokens(UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= tokenizer.build_inputs_with_special_tokens(UpperCamelCase					,						UpperCamelCase      )

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
								    tokenizer.sep_token_id
								]