






"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase_		:			List[str]				   =					logging.get_logger(__name__)

lowerCAmelCase_		:			Optional[int]				   =					{
    '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/config.json''',
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}





class      UpperCamelCase_       (				a_     ):
  _A				:    Dict =		'rembert'



  def __init__(					self       ,						snake_case__=25_03_00       ,						snake_case__=11_52       ,						snake_case__=32       ,						snake_case__=18       ,						snake_case__=2_56       ,						snake_case__=16_64       ,						snake_case__=46_08       ,						snake_case__="gelu"       ,						snake_case__=0.0       ,						snake_case__=0.0       ,						snake_case__=0.1       ,						snake_case__=5_12       ,						snake_case__=2       ,						snake_case__=0.02       ,						snake_case__=1e-12       ,						snake_case__=True       ,						snake_case__=0       ,						snake_case__=3_12       ,						snake_case__=3_13       ,						**snake_case__       ,						)	->	int:



         """simple docstring"""





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

         UpperCAmelCase					=	vocab_size
         UpperCAmelCase					=	input_embedding_size
         UpperCAmelCase					=	output_embedding_size
         UpperCAmelCase					=	max_position_embeddings
         UpperCAmelCase					=	hidden_size
         UpperCAmelCase					=	num_hidden_layers
         UpperCAmelCase					=	num_attention_heads
         UpperCAmelCase					=	intermediate_size
         UpperCAmelCase					=	hidden_act
         UpperCAmelCase					=	hidden_dropout_prob
         UpperCAmelCase					=	attention_probs_dropout_prob
         UpperCAmelCase					=	classifier_dropout_prob
         UpperCAmelCase					=	initializer_range
         UpperCAmelCase					=	type_vocab_size
         UpperCAmelCase					=	layer_norm_eps
         UpperCAmelCase					=	use_cache
         UpperCAmelCase					=	False





class      UpperCamelCase_       (				a_     ):



  @property
  def 						UpperCamelCase_ (					self )	->	Mapping[str, Mapping[int, str]]:



         """simple docstring"""





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



  @property
  def 						UpperCamelCase_ (					self )	->	float:



         """simple docstring"""





         return 1e-4







"""simple docstring"""
__UpperCamelCase			:		Tuple		    =   10**8

def 						_SCREAMING_SNAKE_CASE       (_UpperCAmelCase :  int       ):
 if n % 10 == 0:
  return False
 lowerCAmelCase  							=      str(_UpperCAmelCase       )
 return s == s[::-1]

def 						_SCREAMING_SNAKE_CASE       ():
 lowerCAmelCase  							=      set()
 lowerCAmelCase  							=      1
 lowerCAmelCase  							=      5
 while sum_squares < LIMIT:
  lowerCAmelCase  							=      first_square + 1
  while sum_squares < LIMIT:
   if is_palindrome(_UpperCAmelCase       ):
    answer.add(_UpperCAmelCase       )
   last_square += 1
   sum_squares += last_square**2
  first_square += 1
  lowerCAmelCase  							=      first_square**2 + (first_square + 1) ** 2

 return sum(_UpperCAmelCase       )


if __name__ == "__main__":
       print(solution())





