




"""simple docstring"""






from __future__ import annotations

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






@dataclass
class lowerCAmelCase__	:






			'''simple docstring'''



			lowerCamelCase__      =			42
			lowerCamelCase__      =			42






class lowerCAmelCase__	:






			'''simple docstring'''



			def __init__(  self  ,      lowercase  ):
							_lowerCamelCase     :			list[list[Edge]]    =    [[] for _ in range(__lowerCamelCase  )]
							_lowerCamelCase     :			Optional[int]    =    size
			def __getitem__(  self  ,      lowercase  ):
							return iter(self._graph[vertex]  )
			@property
			def 					A_    (  self  ):
							return self._size
			def 					A_    (  self  ,      lowercase  ,      lowercase  ,      lowercase  ):




							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(__lowerCamelCase  ,      __lowerCamelCase  )  )






			def 					A_    (  self  ,      lowercase  ,      lowercase  ):
							_lowerCamelCase     :			str    =    deque([start_vertex]  )
							_lowerCamelCase     :			list[int | None]    =    [None] * self.size
							_lowerCamelCase     :			List[Any]    =    0

							while queue:
											_lowerCamelCase     :			Union[str, Any]    =    queue.popleft()
											_lowerCamelCase     :			Union[str, Any]    =    distances[current_vertex]
											if current_distance is None:
															continue

											for edge in self[current_vertex]:
															_lowerCamelCase     :			int    =    current_distance + edge.weight
															_lowerCamelCase     :			Any    =    distances[edge.destination_vertex]
															if (
															    isinstance(__lowerCamelCase  ,      __lowerCamelCase  )
															    and new_distance >= dest_vertex_distance
															):
																			continue
															_lowerCamelCase     :			List[str]    =    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()






"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a_ =			logging.get_logger(__name__)

a_ =			{
    """roberta-base""": """https://huggingface.co/roberta-base/resolve/main/config.json""",
    """roberta-large""": """https://huggingface.co/roberta-large/resolve/main/config.json""",
    """roberta-large-mnli""": """https://huggingface.co/roberta-large-mnli/resolve/main/config.json""",
    """distilroberta-base""": """https://huggingface.co/distilroberta-base/resolve/main/config.json""",
    """roberta-base-openai-detector""": """https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json""",
    """roberta-large-openai-detector""": """https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json""",
}






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 _lowerCamelCase        =     """roberta"""

 def __init__(    self					,						__lowerCamelCase=5_0265					,						__lowerCamelCase=768					,						__lowerCamelCase=12					,						__lowerCamelCase=12					,						__lowerCamelCase=3072					,						__lowerCamelCase="gelu"					,						__lowerCamelCase=0.1					,						__lowerCamelCase=0.1					,						__lowerCamelCase=512					,						__lowerCamelCase=2					,						__lowerCamelCase=0.0_2					,						__lowerCamelCase=1e-1_2					,						__lowerCamelCase=1					,						__lowerCamelCase=0					,						__lowerCamelCase=2					,						__lowerCamelCase="absolute"					,						__lowerCamelCase=True					,						__lowerCamelCase=None					,						**__lowerCamelCase					,						):



     '''simple docstring'''




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

     __A    :						str						 =     vocab_size
     __A    :						Any						 =     hidden_size
     __A    :						Any						 =     num_hidden_layers
     __A    :						int						 =     num_attention_heads
     __A    :						List[Any]						 =     hidden_act
     __A    :						Any						 =     intermediate_size
     __A    :						List[str]						 =     hidden_dropout_prob
     __A    :						List[Any]						 =     attention_probs_dropout_prob
     __A    :						Optional[Any]						 =     max_position_embeddings
     __A    :						str						 =     type_vocab_size
     __A    :						int						 =     initializer_range
     __A    :						Tuple						 =     layer_norm_eps
     __A    :						str						 =     position_embedding_type
     __A    :						int						 =     use_cache
     __A    :						Optional[int]						 =     classifier_dropout






class 		__snake_case					(		SCREAMING_SNAKE_CASE__     ):





 """simple docstring"""


 @property
 def 					UpperCamelCase__(    self  ):



     '''simple docstring'''




     if self.task == "multiple-choice":
         __A    :						List[Any]						 =     {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
     else:
         __A    :						Optional[Any]						 =     {0: '''batch''', 1: '''sequence'''}
     return OrderedDict(
         [
             ('''input_ids''', dynamic_axis),
             ('''attention_mask''', dynamic_axis),
         ]  )




