


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


snake_case_						:			Dict													=							logging.get_logger(__name__)

snake_case_						:			int													=							{
    '''facebook/dpr-ctx_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-ctx_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'''
    ),
}

class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						"dpr"




						def __init__(       self					:      Dict				,    _a					:      Any=3_0522				,    _a					:      List[str]=768				,    _a					:      List[str]=12				,    _a					:      int=12				,    _a					:      Union[str, Any]=3072				,    _a					:      List[Any]="gelu"				,    _a					:      Tuple=0.1				,    _a					:      List[Any]=0.1				,    _a					:      Optional[Any]=512				,    _a					:      Union[str, Any]=2				,    _a					:      Any=0.02				,    _a					:      Union[str, Any]=1E-12				,    _a					:      List[Any]=0				,    _a					:      int="absolute"				,    _a					:      int = 0				,    **_a					:      Optional[Any]				,    )							->     Dict:


										"""simple docstring"""





										super().__init__(pad_token_id=_a				,    **_a  )

										_SCREAMING_SNAKE_CASE			  =vocab_size
										_SCREAMING_SNAKE_CASE			  =hidden_size
										_SCREAMING_SNAKE_CASE			  =num_hidden_layers
										_SCREAMING_SNAKE_CASE			  =num_attention_heads
										_SCREAMING_SNAKE_CASE			  =hidden_act
										_SCREAMING_SNAKE_CASE			  =intermediate_size
										_SCREAMING_SNAKE_CASE			  =hidden_dropout_prob
										_SCREAMING_SNAKE_CASE			  =attention_probs_dropout_prob
										_SCREAMING_SNAKE_CASE			  =max_position_embeddings
										_SCREAMING_SNAKE_CASE			  =type_vocab_size
										_SCREAMING_SNAKE_CASE			  =initializer_range
										_SCREAMING_SNAKE_CASE			  =layer_norm_eps
										_SCREAMING_SNAKE_CASE			  =projection_dim
										_SCREAMING_SNAKE_CASE			  =position_embedding_type



from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


snake_case_						:			List[Any]													=							logging.get_logger(__name__)

snake_case_						:			Optional[Any]													=							'''T5Config'''

class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						"mt5"
						UpperCAmelCase             =						MTaConfig

class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						"mt5"
						UpperCAmelCase             =						MTaConfig

class 						A__							(		UpperCamelCase__  ):
						UpperCAmelCase             =						"mt5"
						UpperCAmelCase             =						MTaConfig