

import copy

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


lowerCAmelCase							:						Optional[Any]     			=		logging.get_logger(__name__)



class 						__lowercase       (				UpperCAmelCase_			):




			"""simple docstring"""







			_UpperCAmelCase     :							str    							=  '''speech-encoder-decoder'''
			_UpperCAmelCase     :							List[Any]    							=  True



			def __init__(				self						:  Optional[Any]     ,		**lowerCAmelCase__						:  str):
									super().__init__(**lowerCAmelCase__)
									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}")

									SCREAMING_SNAKE_CASE_:				int							= kwargs.pop("encoder")
									SCREAMING_SNAKE_CASE_:				Optional[Any]							= encoder_config.pop("model_type")
									SCREAMING_SNAKE_CASE_:				Union[str, Any]							= kwargs.pop("decoder")
									SCREAMING_SNAKE_CASE_:				Union[str, Any]							= decoder_config.pop("model_type")

									SCREAMING_SNAKE_CASE_:				str							= AutoConfig.for_model(lowerCAmelCase__     ,		**lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_:				Union[str, Any]							= AutoConfig.for_model(lowerCAmelCase__     ,		**lowerCAmelCase__)
									SCREAMING_SNAKE_CASE_:				Union[str, Any]							= True



			@classmethod
			def  _SCREAMING_SNAKE_CASE    (				cls						:  Dict     ,		lowerCAmelCase__						:  PretrainedConfig     ,		lowerCAmelCase__						:  PretrainedConfig     ,		**lowerCAmelCase__						:  str):
									logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config")
									SCREAMING_SNAKE_CASE_:				int							= True
									SCREAMING_SNAKE_CASE_:				Optional[Any]							= True

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




			def  _SCREAMING_SNAKE_CASE    (				self						:  str):
									SCREAMING_SNAKE_CASE_:				List[str]							= copy.deepcopy(self.__dict__)
									SCREAMING_SNAKE_CASE_:				Optional[int]							= self.encoder.to_dict()
									SCREAMING_SNAKE_CASE_:				Dict							= self.decoder.to_dict()
									SCREAMING_SNAKE_CASE_:				List[str]							= self.__class__.model_type
									return output









def     A_   (					_UpperCAmelCase					):
						SCREAMING_SNAKE_CASE_:				Optional[Any]							= []
						SCREAMING_SNAKE_CASE_:				Any							= 1

						for i in range(len(_UpperCAmelCase					)					):
												if i + 1 < len(_UpperCAmelCase					) and text[i] == text[i + 1]:
																		count += 1
												else:
																		encoded.append((text[i], count)					)
																		SCREAMING_SNAKE_CASE_:				List[Any]							= 1

						return encoded







def     A_   (					_UpperCAmelCase					):
						return "".join(char * length for char, length in encoded					)


if __name__ == "__main__":
						from doctest import testmod

						testmod(name="""run_length_encode""", verbose=True)
						testmod(name="""run_length_decode""", verbose=True)






