





"""simple docstring"""






from queue import PriorityQueue
from typing import Any

import numpy as np

def     __A      (			a_						:int   ,       a_						:List[str]   ,       a_						:Tuple   ,       a_						:List[Any]   ,       a_						:Optional[Any]   ,       a_						:Tuple   ,       a_						:List[Any]   ,       a_						:int   ,       a_						:Optional[int]   ,       )		->		List[str]:
				for nxt, d in graph[v]:
								if nxt in visited_forward:
												continue
								__a :						Optional[Any]			       =  cst_fwd.get(a_   ,       np.inf)
								__a :						Optional[Any]			       =  cst_fwd[v] + d
								if new_cost_f < old_cost_f:
												queue.put((new_cost_f, nxt))
												__a :						List[str]			       =  new_cost_f
												__a :						Any			       =  v
								if nxt in visited_backward:
												if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
																__a :						Union[str, Any]			       =  cst_fwd[v] + d + cst_bwd[nxt]
				return shortest_distance

def     __A      (			a_						:Tuple   ,       a_						:List[Any]   ,       a_						:Optional[int]   ,       a_						:Any)		->		Optional[int]:
				__a :						List[Any]			       =  -1

				__a :						List[str]			       =  set()
				__a :						List[Any]			       =  set()
				__a :						int			       =  {source: 0}
				__a :						List[str]			       =  {destination: 0}
				__a :						Dict			       =  {source: None}
				__a :						int			       =  {destination: None}
				__a :						PriorityQueue[Any]			       =  PriorityQueue()
				__a :						PriorityQueue[Any]			       =  PriorityQueue()

				__a :						Tuple			       =  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():
								__a :						Tuple			       =  queue_forward.get()
								visited_forward.add(a_)

								__a :						Tuple			       =  queue_backward.get()
								visited_backward.add(a_)

								__a :						Dict			       =  pass_and_relaxation(
								    a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       )

								__a :						Tuple			       =  pass_and_relaxation(
								    a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       a_   ,       )

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

				if shortest_distance != np.inf:
								__a :						List[str]			       =  shortest_distance
				return shortest_path_distance


A 			=  {
    '''B''': [['''C''', 1]],
    '''C''': [['''D''', 1]],
    '''D''': [['''F''', 1]],
    '''E''': [['''B''', 1], ['''G''', 2]],
    '''F''': [],
    '''G''': [['''F''', 1]],
}
A 			=  {
    '''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 dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate




@dataclass(frozen=_UpperCamelCase							)
class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  field(default='''language-modeling'''   ,      metadata={'''include_in_asdict_even_if_is_default''': True}							)

					__lowerCAmelCase  =  Features({'''text''': Value('''string'''							)}							)
					__lowerCAmelCase  =  Features({}							)
					__lowerCAmelCase  =  "text"







					@property
					def  _lowerCamelCase		(						self     ):
									return {self.text_column: "text"}