






from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


a_						:     Any	     =		logging.get_logger(__name__)

a_						:     Tuple	     =		'T5Config'





class    lowerCamelCase__  (						UpperCAmelCase_):
     """simple docstring"""



     _A       =			'mt5'
     _A       =			MTaConfig





class    lowerCamelCase__  (						UpperCAmelCase_):
     """simple docstring"""



     _A       =			'mt5'
     _A       =			MTaConfig





class    lowerCamelCase__  (						UpperCAmelCase_):
     """simple docstring"""



     _A       =			'mt5'
     _A       =			MTaConfig




from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass





@dataclass
class    lowerCamelCase__  :
     """simple docstring"""



     _A       =			42
     _A       =			42





class    lowerCamelCase__  :
     """simple docstring"""



     def __init__(self				,			__a    ):






           '''simple docstring'''



           lowerCamelCase								=		[[] for _ in range(__a    )]
           lowerCamelCase								=		size







     def __getitem__(self				,			__a    ):






           '''simple docstring'''



           return iter(self._graph[vertex]    )







     @property
     def 						_a      (self    ):






           '''simple docstring'''



           return self._size







     def 						_a      (self				,			__a				,			__a				,			__a    ):






           '''simple docstring'''



           if weight not in (0, 1):
                 raise ValueError("Edge weight must be either 0 or 1."    )

           if to_vertex < 0 or to_vertex >= self.size:
                 raise ValueError("Vertex indexes must be in [0; size)."    )

           self._graph[from_vertex].append(Edge(__a				,			__a    )    )







     def 						_a      (self				,			__a				,			__a    ):






           '''simple docstring'''



           lowerCamelCase								=		deque([start_vertex]    )
           lowerCamelCase								=		[None] * self.size
           lowerCamelCase								=		0

           while queue:
                 lowerCamelCase								=		queue.popleft()
                 lowerCamelCase								=		distances[current_vertex]
                 if current_distance is None:
                       continue

                 for edge in self[current_vertex]:
                       lowerCamelCase								=		current_distance + edge.weight
                       lowerCamelCase								=		distances[edge.destination_vertex]
                       if (
                           isinstance(__a				,			__a    )
                           and new_distance >= dest_vertex_distance
                       ):
                             continue
                       lowerCamelCase								=		new_distance
                       if edge.weight == 0:
                             queue.appendleft(edge.destination_vertex    )
                       else:
                             queue.append(edge.destination_vertex    )

           if distances[finish_vertex] is None:
                 raise ValueError("No path from start_vertex to finish_vertex."    )

           return distances[finish_vertex]


if __name__ == "__main__":
     import doctest

     doctest.testmod()