




from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase				:		Optional[Any]     =   logging.get_logger(__name__)

lowerCamelCase				:		Tuple     =   {
    "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   A(						__SCREAMING_SNAKE_CASE   ):



 '''simple docstring'''


 UpperCamelCase						   =						'roberta'

 def __init__(				self					:  int						,							A_					:  Tuple=50265						,							A_					:  Optional[int]=768						,							A_					:  Tuple=12						,							A_					:  Dict=12						,							A_					:  Any=3072						,							A_					:  Optional[int]="gelu"						,							A_					:  List[Any]=0.1						,							A_					:  str=0.1						,							A_					:  Union[str, Any]=512						,							A_					:  Dict=2						,							A_					:  Dict=0.02						,							A_					:  Dict=1E-12						,							A_					:  int=1						,							A_					:  Union[str, Any]=0						,							A_					:  Tuple=2						,							A_					:  Union[str, Any]="absolute"						,							A_					:  Any=True						,							A_					:  Optional[Any]=None						,							**A_					:  Optional[Any]						,							)   ->	List[Any]:

       """simple docstring"""






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

       lowerCamelCase_		     =    vocab_size
       lowerCamelCase_		     =    hidden_size
       lowerCamelCase_		     =    num_hidden_layers
       lowerCamelCase_		     =    num_attention_heads
       lowerCamelCase_		     =    hidden_act
       lowerCamelCase_		     =    intermediate_size
       lowerCamelCase_		     =    hidden_dropout_prob
       lowerCamelCase_		     =    attention_probs_dropout_prob
       lowerCamelCase_		     =    max_position_embeddings
       lowerCamelCase_		     =    type_vocab_size
       lowerCamelCase_		     =    initializer_range
       lowerCamelCase_		     =    layer_norm_eps
       lowerCamelCase_		     =    position_embedding_type
       lowerCamelCase_		     =    use_cache
       lowerCamelCase_		     =    classifier_dropout







class   A(						__SCREAMING_SNAKE_CASE   ):



 '''simple docstring'''


 @property
 def 				a__ (				self					:  Optional[int]  )   ->	str:

       """simple docstring"""






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







"""simple docstring"""




def        lowercase							(		lowerCAmelCase__ :     int			) ->      str:
		if number > 0:
				raise ValueError('''input must be a negative integer'''			)
		__a           =			len(bin(lowerCAmelCase__			)[3:]			)
		__a           =			bin(abs(lowerCAmelCase__			) - (1 << binary_number_length)			)[3:]
		__a           =			(
		    (
		        '''1'''
		        + '''0''' * (binary_number_length - len(lowerCAmelCase__			))
		        + twos_complement_number
		    )
		    if number < 0
		    else '''0'''
		)
		return "0b" + twos_complement_number


if __name__ == "__main__":
				import doctest

				doctest.testmod()






