






'''simple docstring'''




import math

def 			UpperCamelCase_							(      _UpperCAmelCase						:   int					)					->					Optional[Any]:


       """simple docstring"""







       if not isinstance(_UpperCAmelCase    ,			_UpperCAmelCase					):
              _UpperCAmelCase  :						str							   =					F"""Input value of [number={number}] must be an integer"""
              raise TypeError(_UpperCAmelCase					)
       if number < 1:
              _UpperCAmelCase  :						Tuple							   =					F"""Input value of [number={number}] must be a positive integer"""
              raise ValueError(_UpperCAmelCase					)
       _UpperCAmelCase  :						Tuple							   =					[number]
       while number != 1:
              if number % 2 == 0:
                     _UpperCAmelCase  :						Optional[int]							   =					math.floor(math.sqrt(_UpperCAmelCase					)					)
              else:
                     _UpperCAmelCase  :						Union[str, Any]							   =					math.floor(
                         math.sqrt(_UpperCAmelCase					) * math.sqrt(_UpperCAmelCase					) * math.sqrt(_UpperCAmelCase					)					)
              sequence.append(_UpperCAmelCase					)
       return sequence


if __name__ == "__main__":
  import doctest

  doctest.testmod()


'''simple docstring'''




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


__SCREAMING_SNAKE_CASE :  Optional[int]  =						logging.get_logger(__name__)

class 			lowerCamelCase_			(snake_case__					):
      '''simple docstring'''

      __UpperCamelCase:						List[Any]      			=		"speech-encoder-decoder"
      __UpperCamelCase:						Optional[int]      			=		True




      def __init__( self		:       Optional[int]		,      **A		:       Tuple ):
             super().__init__(**A )
             if "encoder" not in kwargs or "decoder" not in kwargs:
                    raise ValueError(
                        F"""A configuraton of type {self.model_type} cannot be instantiated because not both `encoder` and"""
                        F""" `decoder` sub-configurations are passed, but only {kwargs}""" )

             _UpperCAmelCase  :						Dict							   =					kwargs.pop("encoder" )
             _UpperCAmelCase  :						Any							   =					encoder_config.pop("model_type" )
             _UpperCAmelCase  :						str							   =					kwargs.pop("decoder" )
             _UpperCAmelCase  :						int							   =					decoder_config.pop("model_type" )

             _UpperCAmelCase  :						List[Any]							   =					AutoConfig.for_model(A		,      **A )
             _UpperCAmelCase  :						str							   =					AutoConfig.for_model(A		,      **A )
             _UpperCAmelCase  :						Optional[int]							   =					True




      @classmethod
      def   _A			( cls		:       int		,      A		:       PretrainedConfig		,      A		:       PretrainedConfig		,      **A		:       Dict ):
             logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config" )
             _UpperCAmelCase  :						Any							   =					True
             _UpperCAmelCase  :						Union[str, Any]							   =					True

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





      def   _A			( self		:       Tuple ):
             _UpperCAmelCase  :						List[str]							   =					copy.deepcopy(self.__dict__ )
             _UpperCAmelCase  :						Any							   =					self.encoder.to_dict()
             _UpperCAmelCase  :						Union[str, Any]							   =					self.decoder.to_dict()
             _UpperCAmelCase  :						Union[str, Any]							   =					self.__class__.model_type
             return output

