
"""simple docstring"""



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


UpperCAmelCase__          = logging.get_logger(__name__)

UpperCAmelCase__          = {
    '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       lowerCAmelCase__				(						A_	):
     __a						=					"""pegasus"""
     __a						=					["""past_key_values"""]
     __a						=					{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}







     def __init__(							self			:			int    ,      _lowerCamelCase			:			Optional[Any]=50265    ,      _lowerCamelCase			:			Tuple=1024    ,      _lowerCamelCase			:			Optional[Any]=12    ,      _lowerCamelCase			:			Any=4096    ,      _lowerCamelCase			:			List[str]=16    ,      _lowerCamelCase			:			Optional[int]=12    ,      _lowerCamelCase			:			Any=4096    ,      _lowerCamelCase			:			str=16    ,      _lowerCamelCase			:			int=0.0    ,      _lowerCamelCase			:			int=0.0    ,      _lowerCamelCase			:			Union[str, Any]=True    ,      _lowerCamelCase			:			Union[str, Any]=True    ,      _lowerCamelCase			:			Optional[int]="gelu"    ,      _lowerCamelCase			:			str=1024    ,      _lowerCamelCase			:			Any=0.1    ,      _lowerCamelCase			:			Any=0.0    ,      _lowerCamelCase			:			List[str]=0.0    ,      _lowerCamelCase			:			Optional[int]=0.0_2    ,      _lowerCamelCase			:			str=0    ,      _lowerCamelCase			:			Any=False    ,      _lowerCamelCase			:			int=0    ,      _lowerCamelCase			:			Optional[int]=1    ,      _lowerCamelCase			:			Union[str, Any]=1    ,      **_lowerCamelCase			:			str    ,      ):
       _snake_case					     =       vocab_size
       _snake_case					     =       max_position_embeddings
       _snake_case					     =       d_model
       _snake_case					     =       encoder_ffn_dim
       _snake_case					     =       encoder_layers
       _snake_case					     =       encoder_attention_heads
       _snake_case					     =       decoder_ffn_dim
       _snake_case					     =       decoder_layers
       _snake_case					     =       decoder_attention_heads
       _snake_case					     =       dropout
       _snake_case					     =       attention_dropout
       _snake_case					     =       activation_dropout
       _snake_case					     =       activation_function
       _snake_case					     =       init_std
       _snake_case					     =       encoder_layerdrop
       _snake_case					     =       decoder_layerdrop
       _snake_case					     =       use_cache
       _snake_case					     =       encoder_layers
       _snake_case					     =       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      lowercase	(							self			:			List[Any]			):
       return self.encoder_attention_heads







     @property
     def      lowercase	(							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() = }")



