






'''simple docstring'''




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_												=					{
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}

class    _UpperCAmelCase			(     snake_case_						):




   """simple docstring"""

   snake_case    				=						'''roberta-prelayernorm'''

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





         '''simple docstring'''





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

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





class    _UpperCAmelCase			(     snake_case_						):




   """simple docstring"""

   @property
   def 						lowerCAmelCase (		self :	str		):





         '''simple docstring'''





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










'''simple docstring'''




from string import ascii_lowercase, ascii_uppercase



def 	a			( lowerCamelCase__    ):
			'''simple docstring'''





			if not sentence:
						return ""
			A_	:						Optional[int]	=     dict(zip(lowerCamelCase__						,      lowerCamelCase__    )    )
			return lower_to_upper.get(sentence[0]						,      sentence[0]    ) + sentence[1:]


if __name__ == "__main__":
						from doctest import testmod

						testmod()