




from collections import OrderedDict
from typing import Mapping

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


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

UpperCamelCase__ :   Union[str, Any]						=							{
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}







class 				lowerCAmelCase_       (					lowerCamelCase_							):
				__a     :       int						=     "roberta-prelayernorm"






				def __init__(			self      ,snake_case__=50265      ,snake_case__=768      ,snake_case__=12      ,snake_case__=12      ,snake_case__=3072      ,snake_case__="gelu"      ,snake_case__=0.1      ,snake_case__=0.1      ,snake_case__=512      ,snake_case__=2      ,snake_case__=0.02      ,snake_case__=1E-12      ,snake_case__=1      ,snake_case__=0      ,snake_case__=2      ,snake_case__="absolute"      ,snake_case__=True      ,snake_case__=None      ,**snake_case__      ,):
							super().__init__(pad_token_id=snake_case__      ,bos_token_id=snake_case__      ,eos_token_id=snake_case__      ,**snake_case__ )

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







class 				lowerCAmelCase_       (					lowerCamelCase_							):






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











'''simple docstring'''



def 				lowercase_					(     __A			:							int       ,   __A			:							int      )							->   int:



 """simple docstring"""




 return 1 if input_a == input_a else 0


def 				lowercase_					(     )							->   None:



 """simple docstring"""




 assert xnor_gate(0       ,   0      ) == 1
 assert xnor_gate(0       ,   1      ) == 0
 assert xnor_gate(1       ,   0      ) == 0
 assert xnor_gate(1       ,   1      ) == 1


if __name__ == "__main__":
      print(xnor_gate(0, 0))
      print(xnor_gate(0, 1))
      print(xnor_gate(1, 0))
      print(xnor_gate(1, 1))



