




'''simple docstring'''





import copy

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


UpperCamelCase_		:    List[str]									=		logging.get_logger(__name__)

class      _a       (		__lowerCAmelCase							):
					SCREAMING_SNAKE_CASE_							:					Optional[int]					       =		"""speech-encoder-decoder"""
					SCREAMING_SNAKE_CASE_							:					Tuple					       =		True






					def __init__(				self      ,**_SCREAMING_SNAKE_CASE					)							->    int:
										super().__init__(**_SCREAMING_SNAKE_CASE					)
										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}"""					)

										_snake_case							=   kwargs.pop("encoder"					)
										_snake_case							=   encoder_config.pop("model_type"					)
										_snake_case							=   kwargs.pop("decoder"					)
										_snake_case							=   decoder_config.pop("model_type"					)

										_snake_case							=   AutoConfig.for_model(_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)
										_snake_case							=   AutoConfig.for_model(_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)
										_snake_case							=   True






					@classmethod
					def        _lowercase			(				cls      ,_SCREAMING_SNAKE_CASE      ,_SCREAMING_SNAKE_CASE      ,**_SCREAMING_SNAKE_CASE					)							->    PretrainedConfig:
										logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"					)
										_snake_case							=   True
										_snake_case							=   True

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






					def        _lowercase			(				self					)							->    int:
										_snake_case							=   copy.deepcopy(self.__dict__					)
										_snake_case							=   self.encoder.to_dict()
										_snake_case							=   self.decoder.to_dict()
										_snake_case							=   self.__class__.model_type
										return output








'''simple docstring'''





UpperCamelCase_		:    Optional[Any]									=		'''
# Diffusers installation
! pip install diffusers transformers datasets accelerate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/diffusers.git
'''

UpperCamelCase_		:    List[Any]									=		[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]


