



import copy

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


__snake_case						:str						=					logging.get_logger(__name__)

class    _A	(     __lowercase   ):
       UpperCamelCase__  :   Optional[Any]						 =						'''encoder-decoder'''
       UpperCamelCase__  :   List[str]						 =						True



       def __init__(		self							:					Any					,		**__SCREAMING_SNAKE_CASE							:					List[Any]):


           '''simple docstring'''

           super().__init__(**UpperCAmelCase__)
           assert (
               "encoder" in kwargs and "decoder" in kwargs
           ), "Config has to be initialized with encoder and decoder config"
           __a							=    kwargs.pop('''encoder''')
           __a							=    encoder_config.pop('''model_type''')
           __a							=    kwargs.pop('''decoder''')
           __a							=    decoder_config.pop('''model_type''')

           from ..auto.configuration_auto import AutoConfig

           __a							=    AutoConfig.for_model(UpperCAmelCase__					,		**UpperCAmelCase__)
           __a							=    AutoConfig.for_model(UpperCAmelCase__					,		**UpperCAmelCase__)
           __a							=    True



       @classmethod
       def 		_lowerCamelCase      (		cls							:					Union[str, Any]					,		__SCREAMING_SNAKE_CASE							:					PretrainedConfig					,		__SCREAMING_SNAKE_CASE							:					PretrainedConfig					,		**__SCREAMING_SNAKE_CASE							:					Any):


           '''simple docstring'''

           logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config''')
           __a							=    True
           __a							=    True

           return cls(encoder=encoder_config.to_dict()					,		decoder=decoder_config.to_dict()					,		**UpperCAmelCase__)





       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

           __a							=    copy.deepcopy(self.__dict__)
           __a							=    self.encoder.to_dict()
           __a							=    self.decoder.to_dict()
           __a							=    self.__class__.model_type
           return output










def 					__snake_case     (      _UpperCAmelCase = 1000000    ):
    __a							=    limit + 1
    __a							=    [0] * limit
    for first_term in range(1       ,			_UpperCAmelCase    ):
        for n in range(_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase    ):
            __a							=    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							=    sum(1 for x in frequency[1:limit] if x == 10    )

    return count


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





