
"""simple docstring"""

import functools
def 		UpperCAmelCase (		a_,						a_      ):





		'''simple docstring'''


		lowerCamelCase					:      str          =   len(a_      )
		lowerCamelCase					:      Optional[int]          =   len(a_      )

		@functools.cache
		def min_distance(a_,						a_      ) -> int:
				# if first word index is overflow - delete all from the second word
				if indexa >= len_worda:
						return len_worda - indexa
				# if second word index is overflow - delete all from the first word
				if indexa >= len_worda:
						return len_worda - indexa
				lowerCamelCase					:      str          =   int(worda[indexa] != worda[indexa]      )  # current letters not identical
				return min(
				    1 + min_distance(indexa + 1,						a_      ),						1 + min_distance(a_,						indexa + 1      ),						diff + min_distance(indexa + 1,						indexa + 1      ),						)

		return min_distance(0,						0      )


if __name__ == "__main__":
					import doctest

					doctest.testmod()

"""simple docstring"""

import copy

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


_A						=			logging.get_logger(__name__)






class 	_lowercase       (    __UpperCAmelCase		):
	lowercase_				=     'encoder-decoder'
	lowercase_				=     True




	def __init__(			self		,			**UpperCAmelCase_ )		->							str:
			super().__init__(**UpperCAmelCase_ )
			assert (
			    "encoder" in kwargs and "decoder" in kwargs
			), "Config has to be initialized with encoder and decoder config"
			lowerCamelCase					:      List[Any]          =   kwargs.pop('encoder' )
			lowerCamelCase					:      Optional[int]          =   encoder_config.pop('model_type' )
			lowerCamelCase					:      str          =   kwargs.pop('decoder' )
			lowerCamelCase					:      Dict          =   decoder_config.pop('model_type' )

			from ..auto.configuration_auto import AutoConfig

			lowerCamelCase					:      int          =   AutoConfig.for_model(UpperCAmelCase_		,			**UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   AutoConfig.for_model(UpperCAmelCase_		,			**UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   True




	@classmethod
	def       _UpperCamelCase   (			cls		,			UpperCAmelCase_		,			UpperCAmelCase_		,			**UpperCAmelCase_ )		->							PretrainedConfig:
			logger.info('Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config' )
			lowerCamelCase					:      str          =   True
			lowerCamelCase					:      Optional[Any]          =   True

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




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






