"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__					       =	logging.get_logger(__name__)

lowercase__					       =	{
    'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
    'funnel-transformer/small-base': 'https://huggingface.co/funnel-transformer/small-base/resolve/main/config.json',
    'funnel-transformer/medium': 'https://huggingface.co/funnel-transformer/medium/resolve/main/config.json',
    'funnel-transformer/medium-base': 'https://huggingface.co/funnel-transformer/medium-base/resolve/main/config.json',
    'funnel-transformer/intermediate': (
        'https://huggingface.co/funnel-transformer/intermediate/resolve/main/config.json'
    ),
    'funnel-transformer/intermediate-base': (
        'https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/config.json'
    ),
    'funnel-transformer/large': 'https://huggingface.co/funnel-transformer/large/resolve/main/config.json',
    'funnel-transformer/large-base': 'https://huggingface.co/funnel-transformer/large-base/resolve/main/config.json',
    'funnel-transformer/xlarge': 'https://huggingface.co/funnel-transformer/xlarge/resolve/main/config.json',
    'funnel-transformer/xlarge-base': 'https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/config.json',
}




class    __snake_case       (     __lowerCAmelCase				):
      a__        =		"""funnel"""
      a__        =		{
          """hidden_size""": """d_model""",
          """num_attention_heads""": """n_head""",
      }



      def __init__(						self    ,			lowercase=3_05_22    ,			lowercase=[4, 4, 4]    ,			lowercase=None    ,			lowercase=2    ,			lowercase=7_68    ,			lowercase=12    ,			lowercase=64    ,			lowercase=30_72    ,			lowercase="gelu_new"    ,			lowercase=0.1    ,			lowercase=0.1    ,			lowercase=0.0    ,			lowercase=0.1    ,			lowercase=None    ,			lowercase=1e-9    ,			lowercase="mean"    ,			lowercase="relative_shift"    ,			lowercase=True    ,			lowercase=True    ,			lowercase=True    ,			**lowercase    ,			)	->			int:





        '''simple docstring'''





        a__:     Any										=	vocab_size
        a__:     List[str]										=	block_sizes
        a__:     str										=	[1] * len(lowercase) if block_repeats is None else block_repeats
        assert len(lowercase) == len(
            self.block_repeats), "`block_sizes` and `block_repeats` should have the same length."
        a__:     List[Any]										=	num_decoder_layers
        a__:     str										=	d_model
        a__:     Dict										=	n_head
        a__:     List[str]										=	d_head
        a__:     str										=	d_inner
        a__:     List[str]										=	hidden_act
        a__:     List[str]										=	hidden_dropout
        a__:     List[str]										=	attention_dropout
        a__:     Optional[Any]										=	activation_dropout
        a__:     List[str]										=	initializer_range
        a__:     Tuple										=	initializer_std
        a__:     Optional[Any]										=	layer_norm_eps
        assert pooling_type in [
            "mean",
            "max",
        ], f'Got {pooling_type} for `pooling_type` but only \'mean\' and \'max\' are supported.'
        a__:     Optional[Any]										=	pooling_type
        assert attention_type in [
            "relative_shift",
            "factorized",
        ], f'Got {attention_type} for `attention_type` but only \'relative_shift\' and \'factorized\' are supported.'
        a__:     List[str]										=	attention_type
        a__:     Optional[int]										=	separate_cls
        a__:     Optional[Any]										=	truncate_seq
        a__:     List[Any]										=	pool_q_only

        super().__init__(**lowercase)



      @property
      def   lowerCamelCase_   (						self)	->			Optional[int]:





        '''simple docstring'''





        return sum(self.block_sizes)



      @num_hidden_layers.setter
      def   lowerCamelCase_   (						self    ,			lowercase)	->			Optional[Any]:





        '''simple docstring'''





        raise NotImplementedError(
            'This model does not support the setting of `num_hidden_layers`. Please set `block_sizes`.')



      @property
      def   lowerCamelCase_   (						self)	->			Union[str, Any]:





        '''simple docstring'''





        return len(self.block_sizes)



      @num_blocks.setter
      def   lowerCamelCase_   (						self    ,			lowercase)	->			Optional[int]:





        '''simple docstring'''





        raise NotImplementedError('This model does not support the setting of `num_blocks`. Please set `block_sizes`.')



"""simple docstring"""
def 						__a   (	_SCREAMING_SNAKE_CASE = 1000000   )	->int:
  a__:     int										=	limit + 1
  a__:     Optional[int]										=	[0] * limit
  for first_term in range(1		,     _SCREAMING_SNAKE_CASE   ):
    for n in range(_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE   ):
      a__:     List[Any]										=	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

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

  return count


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


