

'''simple docstring'''

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


A_				  =							logging.get_logger(__name__)

A_				  =							{
    "google/pegasus-large": "https://huggingface.co/google/pegasus-large/resolve/main/config.json",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}





class 							_snake_case       (				A_  ):
   _A				:   List[str]			      =    '''pegasus'''
   _A				:   Tuple			      =    ['''past_key_values''']
   _A				:   Any			      =    {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}
   def __init__(       self	:					int   ,SCREAMING_SNAKE_CASE__	:					Optional[Any]=50_265   ,SCREAMING_SNAKE_CASE__	:					Tuple=1_024   ,SCREAMING_SNAKE_CASE__	:					Optional[Any]=12   ,SCREAMING_SNAKE_CASE__	:					Any=4_096   ,SCREAMING_SNAKE_CASE__	:					List[str]=16   ,SCREAMING_SNAKE_CASE__	:					Optional[int]=12   ,SCREAMING_SNAKE_CASE__	:					Any=4_096   ,SCREAMING_SNAKE_CASE__	:					str=16   ,SCREAMING_SNAKE_CASE__	:					int=0.0   ,SCREAMING_SNAKE_CASE__	:					int=0.0   ,SCREAMING_SNAKE_CASE__	:					Union[str, Any]=True   ,SCREAMING_SNAKE_CASE__	:					Union[str, Any]=True   ,SCREAMING_SNAKE_CASE__	:					Optional[int]="gelu"   ,SCREAMING_SNAKE_CASE__	:					str=1_024   ,SCREAMING_SNAKE_CASE__	:					Any=0.1   ,SCREAMING_SNAKE_CASE__	:					Any=0.0   ,SCREAMING_SNAKE_CASE__	:					List[str]=0.0   ,SCREAMING_SNAKE_CASE__	:					Optional[int]=0.02   ,SCREAMING_SNAKE_CASE__	:					str=0   ,SCREAMING_SNAKE_CASE__	:					Any=False   ,SCREAMING_SNAKE_CASE__	:					int=0   ,SCREAMING_SNAKE_CASE__	:					Optional[int]=1   ,SCREAMING_SNAKE_CASE__	:					Union[str, Any]=1   ,**SCREAMING_SNAKE_CASE__	:					str   ,):
     SCREAMING_SNAKE_CASE:List[str]  					=    vocab_size
     SCREAMING_SNAKE_CASE:Any  					=    max_position_embeddings
     SCREAMING_SNAKE_CASE:Dict  					=    d_model
     SCREAMING_SNAKE_CASE:Optional[Any]  					=    encoder_ffn_dim
     SCREAMING_SNAKE_CASE:int  					=    encoder_layers
     SCREAMING_SNAKE_CASE:Optional[int]  					=    encoder_attention_heads
     SCREAMING_SNAKE_CASE:Dict  					=    decoder_ffn_dim
     SCREAMING_SNAKE_CASE:Tuple  					=    decoder_layers
     SCREAMING_SNAKE_CASE:str  					=    decoder_attention_heads
     SCREAMING_SNAKE_CASE:str  					=    dropout
     SCREAMING_SNAKE_CASE:List[Any]  					=    attention_dropout
     SCREAMING_SNAKE_CASE:Tuple  					=    activation_dropout
     SCREAMING_SNAKE_CASE:Dict  					=    activation_function
     SCREAMING_SNAKE_CASE:List[Any]  					=    init_std
     SCREAMING_SNAKE_CASE:Dict  					=    encoder_layerdrop
     SCREAMING_SNAKE_CASE:List[Any]  					=    decoder_layerdrop
     SCREAMING_SNAKE_CASE:Optional[Any]  					=    use_cache
     SCREAMING_SNAKE_CASE:Dict  					=    encoder_layers
     SCREAMING_SNAKE_CASE:Optional[Any]  					=    scale_embedding  # scale factor will be sqrt(d_model) if True
     super().__init__(
         pad_token_id=_lowerCamelCase   ,eos_token_id=_lowerCamelCase   ,is_encoder_decoder=_lowerCamelCase   ,decoder_start_token_id=_lowerCamelCase   ,forced_eos_token_id=_lowerCamelCase   ,**_lowerCamelCase   ,)
   @property
   def 			__UpperCamelCase  (       self	:					List[Any]							):
     return self.encoder_attention_heads







   @property
   def 			__UpperCamelCase  (       self	:					str							):
     return self.d_model








"""simple docstring"""



def 					_UpperCAmelCase      ( __lowerCamelCase   :       int = 1_00_00_00		)     ->					int:
  _snake_case					     =       limit + 1
  _snake_case					     =       [0] * limit
  for first_term in range(1 ,					__lowerCamelCase		):
    for n in range(__lowerCamelCase ,					__lowerCamelCase ,					__lowerCamelCase		):
      _snake_case					     =       first_term + n / first_term
      if common_difference % 4:  # d must be divisble by 4
        continue
      else:
        common_difference /= 4
        if (
            first_term > common_difference
            and first_term < 4 * common_difference
        ):  # since x,y,z are positive integers
          frequency[n] += 1  # so z>0 and a>d ,also 4d<a

  _snake_case					     =       sum(1 for x in frequency[1:limit] if x == 10		)

  return count


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



