





from collections import OrderedDict
from typing import Mapping

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


__lowercase  :   Optional[int]						      =logging.get_logger(__name__)

__lowercase  :   str						      ={
    '''facebook/xlm-roberta-xl''': '''https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json''',
    '''facebook/xlm-roberta-xxl''': '''https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json''',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}


class      A       (	SCREAMING_SNAKE_CASE__						):
      _snake_case							     ='''xlm-roberta-xl'''



      def __init__(	self:						str		,  _lowerCAmelCase:						Optional[int]=25_0880		,  _lowerCAmelCase:						List[str]=2560		,  _lowerCAmelCase:						Any=36		,  _lowerCAmelCase:						List[Any]=32		,  _lowerCAmelCase:						Union[str, Any]=1_0240		,  _lowerCAmelCase:						Union[str, Any]="gelu"		,  _lowerCAmelCase:						Union[str, Any]=0.1		,  _lowerCAmelCase:						Tuple=0.1		,  _lowerCAmelCase:						List[str]=514		,  _lowerCAmelCase:						Tuple=1		,  _lowerCAmelCase:						Any=0.02		,  _lowerCAmelCase:						Optional[Any]=1e-05		,  _lowerCAmelCase:						Optional[int]=1		,  _lowerCAmelCase:						Optional[int]=0		,  _lowerCAmelCase:						Optional[Any]=2		,  _lowerCAmelCase:						Any="absolute"		,  _lowerCAmelCase:						List[str]=True		,  _lowerCAmelCase:						Optional[Any]=None		,  **_lowerCAmelCase:						str		,  )						->    str:
         '''simple docstring'''

         super().__init__(pad_token_id=_lowercase		,  bos_token_id=_lowercase		,  eos_token_id=_lowercase		,  **_lowercase       )
         UpperCAmelCase_											=vocab_size
         UpperCAmelCase_											=hidden_size
         UpperCAmelCase_											=num_hidden_layers
         UpperCAmelCase_											=num_attention_heads
         UpperCAmelCase_											=hidden_act
         UpperCAmelCase_											=intermediate_size
         UpperCAmelCase_											=hidden_dropout_prob
         UpperCAmelCase_											=attention_probs_dropout_prob
         UpperCAmelCase_											=max_position_embeddings
         UpperCAmelCase_											=type_vocab_size
         UpperCAmelCase_											=initializer_range
         UpperCAmelCase_											=layer_norm_eps
         UpperCAmelCase_											=position_embedding_type
         UpperCAmelCase_											=use_cache
         UpperCAmelCase_											=classifier_dropout


class      A       (	SCREAMING_SNAKE_CASE__						):



      @property
      def 	lowerCAmelCase__    (	self:						Optional[int]       )						->    Mapping[str, Mapping[int, str]]:
         '''simple docstring'''

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











from __future__ import annotations




def     a__ (					lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_						,       UpperCAmelCase_											=set(lowercase__  ), [start]

   while stack:
      UpperCAmelCase_											=stack.pop()
      explored.add(lowercase__  )
      # Differences from BFS:
      # 1) pop last element instead of first one
      # 2) add adjacent elements to stack without exploring them
      for adj in reversed(graph[v]  ):
         if adj not in explored:
            stack.append(lowercase__  )
   return explored


__lowercase  :   Dict						      ={
    """A""": ["""B""", """C""", """D"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B""", """D"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E""", """G"""],
    """G""": ["""F"""],
}

if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(depth_first_search(G, """A"""))




