

from ... import PretrainedConfig


__lowercase     : Union[str, Any]       =						{
    '''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}



class 						_A     (				snake_case				):





  '''simple docstring'''



  __lowerCamelCase			:      Union[str, Any]					=   NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
  __lowerCamelCase			:      int					=   '''nezha'''





  def __init__(  self   ,SCREAMING_SNAKE_CASE_=21128   ,SCREAMING_SNAKE_CASE_=768   ,SCREAMING_SNAKE_CASE_=12   ,SCREAMING_SNAKE_CASE_=12   ,SCREAMING_SNAKE_CASE_=3072   ,SCREAMING_SNAKE_CASE_="gelu"   ,SCREAMING_SNAKE_CASE_=0.1   ,SCREAMING_SNAKE_CASE_=0.1   ,SCREAMING_SNAKE_CASE_=512   ,SCREAMING_SNAKE_CASE_=64   ,SCREAMING_SNAKE_CASE_=2   ,SCREAMING_SNAKE_CASE_=0.02   ,SCREAMING_SNAKE_CASE_=1E-12   ,SCREAMING_SNAKE_CASE_=0.1   ,SCREAMING_SNAKE_CASE_=0   ,SCREAMING_SNAKE_CASE_=2   ,SCREAMING_SNAKE_CASE_=3   ,SCREAMING_SNAKE_CASE_=True   ,**SCREAMING_SNAKE_CASE_   ,):

      '''simple docstring'''
      super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_   ,bos_token_id=SCREAMING_SNAKE_CASE_   ,eos_token_id=SCREAMING_SNAKE_CASE_   ,**SCREAMING_SNAKE_CASE_    )

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







'''simple docstring'''
from __future__ import annotations

def 					lowerCamelCase_ ( __UpperCamelCase					:       dict							,    __UpperCamelCase					:       str		)					->	set[str]:







     """simple docstring"""
     _A		,				_A				=							set(__UpperCamelCase		), [start]

     while stack:
          _A				=							stack.pop()
          explored.add(__UpperCamelCase		)
          # 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(__UpperCamelCase		)
     return explored


lowerCAmelCase						=					{
    """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"""))





