

import copy

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


SCREAMING_SNAKE_CASE						:int      =			logging.get_logger(__name__)






class 		__magic_name__ (				snake_case							):
     UpperCamelCase_     :Union[str, Any]									=	"""speech-encoder-decoder"""
     UpperCamelCase_     :Tuple									=	True






     def __init__(							self						,		**_lowercase     )->			Any:
         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_          =		kwargs.pop("encoder"     )
         UpperCamelCase_          =		encoder_config.pop("model_type"     )
         UpperCamelCase_          =		kwargs.pop("decoder"     )
         UpperCamelCase_          =		decoder_config.pop("model_type"     )

         UpperCamelCase_          =		AutoConfig.for_model(__A						,		**__A     )
         UpperCamelCase_          =		AutoConfig.for_model(__A						,		**__A     )
         UpperCamelCase_          =		True






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

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






     def      UpperCAmelCase_							(							self     )->			Any:
         UpperCamelCase_          =		copy.deepcopy(self.__dict__     )
         UpperCamelCase_          =		self.encoder.to_dict()
         UpperCamelCase_          =		self.decoder.to_dict()
         UpperCamelCase_          =		self.__class__.model_type
         return output








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


__A          = logging.get_logger(__name__)

__A          = {
    'uw-madison/nystromformer-512': 'https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}





class   SCREAMING_SNAKE_CASE (       snake_case    ):





							"""simple docstring"""

							A_       =    "nystromformer"

							def __init__(     self:      List[str]						,   __A:      Dict=3_00_00						,   __A:      int=7_68						,   __A:      int=12						,   __A:      Union[str, Any]=12						,   __A:      List[str]=30_72						,   __A:      Tuple="gelu_new"						,   __A:      Optional[Any]=0.1						,   __A:      Union[str, Any]=0.1						,   __A:      int=5_10						,   __A:      List[Any]=2						,   __A:      List[Any]=64						,   __A:      Optional[Any]=64						,   __A:      str=65						,   __A:      List[str]=False						,   __A:      Tuple=0.02						,   __A:      Dict=1e-5						,   __A:      int=1						,   __A:      str=0						,   __A:      int=2						,   **__A:      Union[str, Any]						,   )			-> int:
												_A									=       vocab_size
												_A									=       max_position_embeddings
												_A									=       hidden_size
												_A									=       num_hidden_layers
												_A									=       num_attention_heads
												_A									=       intermediate_size
												_A									=       hidden_act
												_A									=       hidden_dropout_prob
												_A									=       attention_probs_dropout_prob
												_A									=       initializer_range
												_A									=       type_vocab_size
												_A									=       segment_means_seq_len
												_A									=       num_landmarks
												_A									=       conv_kernel_size
												_A									=       inv_coeff_init_option
												_A									=       layer_norm_eps
												super().__init__(pad_token_id=__A						,   bos_token_id=__A						,   eos_token_id=__A						,   **__A      )



