





from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A :   Any  			=  logging.get_logger(__name__)

_A :   int  			=  {
    'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}


class        __SCREAMING_SNAKE_CASE      (			lowerCAmelCase_ ):
       _UpperCAmelCase				:  Tuple			   =   "roc_bert"







       def __init__(				self					:     Dict		, A					:     List[str]=3_0_5_2_2		, A					:     Optional[Any]=7_6_8		, A					:     Union[str, Any]=1_2		, A					:     Tuple=1_2		, A					:     Dict=3_0_7_2		, A					:     Any="gelu"		, A					:     Dict=0.1		, A					:     Any=0.1		, A					:     Union[str, Any]=5_1_2		, A					:     Optional[Any]=2		, A					:     List[Any]=0.02		, A					:     Optional[int]=1e-12		, A					:     str=True		, A					:     List[str]=0		, A					:     Optional[Any]="absolute"		, A					:     Optional[int]=None		, A					:     Dict=True		, A					:     Union[str, Any]=True		, A					:     Union[str, Any]=7_6_8		, A					:     Union[str, Any]=9_1_0		, A					:     Dict=5_1_2		, A					:     List[str]=2_4_8_5_8		, A					:     List[str]=True		, **A					:     List[str]		, )       ->Any:
          lowerCamelCase__       :						Tuple        =							vocab_size
          lowerCamelCase__       :						Tuple        =							max_position_embeddings
          lowerCamelCase__       :						Dict        =							hidden_size
          lowerCamelCase__       :						List[Any]        =							num_hidden_layers
          lowerCamelCase__       :						List[Any]        =							num_attention_heads
          lowerCamelCase__       :						List[str]        =							intermediate_size
          lowerCamelCase__       :						List[str]        =							hidden_act
          lowerCamelCase__       :						Optional[Any]        =							hidden_dropout_prob
          lowerCamelCase__       :						Union[str, Any]        =							attention_probs_dropout_prob
          lowerCamelCase__       :						Any        =							initializer_range
          lowerCamelCase__       :						Tuple        =							type_vocab_size
          lowerCamelCase__       :						int        =							layer_norm_eps
          lowerCamelCase__       :						int        =							use_cache
          lowerCamelCase__       :						str        =							enable_pronunciation
          lowerCamelCase__       :						Optional[int]        =							enable_shape
          lowerCamelCase__       :						int        =							pronunciation_embed_dim
          lowerCamelCase__       :						Union[str, Any]        =							pronunciation_vocab_size
          lowerCamelCase__       :						int        =							shape_embed_dim
          lowerCamelCase__       :						str        =							shape_vocab_size
          lowerCamelCase__       :						Union[str, Any]        =							concat_input
          lowerCamelCase__       :						Any        =							position_embedding_type
          lowerCamelCase__       :						List[str]        =							classifier_dropout
          super().__init__(pad_token_id=A		, **A      )










from math import ceil, sqrt



def 	_a						(   UpperCAmelCase = 1000000					)    ->    int:







   """simple docstring"""
   lowerCamelCase__       :						Any        =							0

   for outer_width in range(3      ,  (limit // 4) + 2					):
      if outer_width**2 > limit:
         lowerCamelCase__       :						List[Any]        =							max(ceil(sqrt(outer_width**2 - limit					)					)      ,  1					)
      else:
         lowerCamelCase__       :						Union[str, Any]        =							1
      if (outer_width - hole_width_lower_bound) % 2:
         hole_width_lower_bound += 1

      answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

   return answer


if __name__ == "__main__":
       print(F'''{solution() = }''')



