


from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase   	=  logging.get_logger(__name__)

__lowerCamelCase   	=  {
    '''flaubert/flaubert_small_cased''': '''https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json''',
    '''flaubert/flaubert_base_uncased''': '''https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json''',
    '''flaubert/flaubert_base_cased''': '''https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json''',
    '''flaubert/flaubert_large_cased''': '''https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json''',
}


class 	a__						(    lowerCAmelCase_     ):
       lowerCamelCase__:  str				     =  """flaubert"""
       lowerCamelCase__:  str				     =  {
           """hidden_size""": """emb_dim""",
           """num_attention_heads""": """n_heads""",
           """num_hidden_layers""": """n_layers""",
           """n_words""": """vocab_size""",  # For backward compatibility
       }

       def __init__( self   :  List[Any]   ,				lowerCamelCase_   :  str=False   ,				lowerCamelCase_   :  List[Any]=0.0   ,				lowerCamelCase_   :  int=3_0_1_4_5   ,				lowerCamelCase_   :  str=2_0_4_8   ,				lowerCamelCase_   :  Dict=1_2   ,				lowerCamelCase_   :  Any=1_6   ,				lowerCamelCase_   :  Optional[int]=0.1   ,				lowerCamelCase_   :  Tuple=0.1   ,				lowerCamelCase_   :  List[str]=True   ,				lowerCamelCase_   :  str=False   ,				lowerCamelCase_   :  int=False   ,				lowerCamelCase_   :  Optional[int]=False   ,				lowerCamelCase_   :  Tuple=1   ,				lowerCamelCase_   :  Union[str, Any]=True   ,				lowerCamelCase_   :  str=5_1_2   ,				lowerCamelCase_   :  Optional[Any]=2_0_4_8**-0.5   ,				lowerCamelCase_   :  Optional[int]=1E-12   ,				lowerCamelCase_   :  int=0.0_2   ,				lowerCamelCase_   :  int=0   ,				lowerCamelCase_   :  Optional[int]=1   ,				lowerCamelCase_   :  Dict=2   ,				lowerCamelCase_   :  int=3   ,				lowerCamelCase_   :  str=5   ,				lowerCamelCase_   :  Optional[int]=True   ,				lowerCamelCase_   :  Union[str, Any]="first"   ,				lowerCamelCase_   :  int=True   ,				lowerCamelCase_   :  Dict=None   ,				lowerCamelCase_   :  Union[str, Any]=True   ,				lowerCamelCase_   :  str=0.1   ,				lowerCamelCase_   :  str=5   ,				lowerCamelCase_   :  Any=5   ,				lowerCamelCase_   :  int=0   ,				lowerCamelCase_   :  Any=0   ,				lowerCamelCase_   :  Tuple=2   ,				lowerCamelCase_   :  Optional[Any]=0   ,				**lowerCamelCase_   :  int   ,				):
            a_     :  Dict				      =     pre_norm
            a_     :  List[str]				      =     layerdrop
            a_     :  Any				      =     vocab_size
            a_     :  Tuple				      =     emb_dim
            a_     :  str				      =     n_layers
            a_     :  Tuple				      =     n_heads
            a_     :  List[Any]				      =     dropout
            a_     :  str				      =     attention_dropout
            a_     :  Dict				      =     gelu_activation
            a_     :  Optional[Any]				      =     sinusoidal_embeddings
            a_     :  List[str]				      =     causal
            a_     :  Union[str, Any]				      =     asm
            a_     :  int				      =     n_langs
            a_     :  int				      =     use_lang_emb
            a_     :  int				      =     layer_norm_eps
            a_     :  Dict				      =     bos_index
            a_     :  int				      =     eos_index
            a_     :  Dict				      =     pad_index
            a_     :  Dict				      =     unk_index
            a_     :  Tuple				      =     mask_index
            a_     :  Tuple				      =     is_encoder
            a_     :  Dict				      =     max_position_embeddings
            a_     :  Union[str, Any]				      =     embed_init_std
            a_     :  List[str]				      =     init_std
            a_     :  Union[str, Any]				      =     summary_type
            a_     :  Tuple				      =     summary_use_proj
            a_     :  int				      =     summary_activation
            a_     :  Union[str, Any]				      =     summary_proj_to_labels
            a_     :  List[str]				      =     summary_first_dropout
            a_     :  Optional[int]				      =     start_n_top
            a_     :  List[Any]				      =     end_n_top
            a_     :  Dict				      =     mask_token_id
            a_     :  List[Any]				      =     lang_id

            if "n_words" in kwargs:
                 a_     :  Any				      =     kwargs["""n_words"""]

            super().__init__(pad_token_id=lowerCamelCase_   ,				bos_token_id=lowerCamelCase_   ,				**lowerCamelCase_     )


class 	a__						(    lowerCAmelCase_     ):

       @property
       def     UpperCAmelCase( self   :  Tuple     ):
            if self.task == "multiple-choice":
                 a_     :  Optional[Any]				      =     {0: """batch""", 1: """choice""", 2: """sequence"""}
            else:
                 a_     :  List[Any]				      =     {0: """batch""", 1: """sequence"""}
            return OrderedDict(
                [
                    ("""input_ids""", dynamic_axis),
                    ("""attention_mask""", dynamic_axis),
                ]     )







class 	a__						:

       def __init__( self   :  int   ,				lowerCamelCase_   :  int     ):
            a_     :  Dict				      =     data
            a_     :  int
            a_     :  Node



def 			_a      (    __UpperCamelCase			):
     a_     :  int				      =     0
     a_     :  Optional[Any]				      =     x



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase			):
     a_      ,      a_     :  Dict				      =     find_set(__UpperCamelCase			), find_set(__UpperCamelCase			)
     if x == y:
          return

     elif x.rank > y.rank:
          a_     :  Tuple				      =     x
     else:
          a_     :  Optional[Any]				      =     y
          if x.rank == y.rank:
               y.rank += 1



def 			_a      (    __UpperCamelCase			):
     if x != x.parent:
          a_     :  Tuple				      =     find_set(x.parent			)
     return x.parent



def 			_a      (    __UpperCamelCase			):
     a_     :  List[Any]				      =     ({0, 1, 2}, {3, 4, 5})
     for s in sets:
          if node.data in s:
               return s
     a_     :  Union[str, Any]				      =     F'''{node.data} is not in {sets}'''
     raise ValueError(__UpperCamelCase			)



def 			_a      (    ):
     a_     :  int				      =     [Node(__UpperCamelCase			) for i in range(6			)]
     for v in vertex:
          make_set(__UpperCamelCase			)

     union_set(vertex[0]	,	vertex[1]			)
     union_set(vertex[1]	,	vertex[2]			)
     union_set(vertex[3]	,	vertex[4]			)
     union_set(vertex[3]	,	vertex[5]			)

     for nodea in vertex:
          for nodea in vertex:
               if find_python_set(__UpperCamelCase			).isdisjoint(find_python_set(__UpperCamelCase			)			):
                    assert find_set(__UpperCamelCase			) != find_set(__UpperCamelCase			)
               else:
                    assert find_set(__UpperCamelCase			) == find_set(__UpperCamelCase			)


if __name__ == "__main__":
       test_disjoint_set()



