
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       ='''ClapFeatureExtractor'''
 lowerCamelCase				       =('''RobertaTokenizer''', '''RobertaTokenizerFast''')
 def __init__(   self			:    Dict				,   lowerCamelCase			:    int				,   lowerCamelCase			:    int       ):



   """simple docstring"""





   super().__init__(lowerCamelCase				,   lowerCamelCase       )
 def __call__(   self			:    Optional[int]				,   lowerCamelCase			:    Optional[Any]=None				,   lowerCamelCase			:    str=None				,   lowerCamelCase			:    List[Any]=None				,   **lowerCamelCase			:    List[Any]       ):



   """simple docstring"""





   __A		:     int												=		kwargs.pop("""sampling_rate"""				,   lowerCamelCase       )

   if text is None and audios is None:
     raise ValueError("""You have to specify either text or audios. Both cannot be none."""       )

   if text is not None:
     __A		:     Union[str, Any]												=		self.tokenizer(lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if audios is not None:
     __A		:     Dict												=		self.feature_extractor(
         lowerCamelCase				,   sampling_rate=lowerCamelCase				,   return_tensors=lowerCamelCase				,   **lowerCamelCase       )

   if text is not None and audios is not None:
     __A		:     Optional[int]												=		audio_features.input_features
     return encoding
   elif text is not None:
     return encoding
   else:
     return BatchEncoding(data=dict(**lowerCamelCase       )				,   tensor_type=lowerCamelCase       )
 def 		lowercase_(   self			:    Any				,   *lowerCamelCase			:    List[Any]				,   **lowerCamelCase			:    Tuple       ):



   """simple docstring"""





   return self.tokenizer.batch_decode(*lowerCamelCase				,   **lowerCamelCase       )
 def 		lowercase_(   self			:    int				,   *lowerCamelCase			:    str				,   **lowerCamelCase			:    Optional[Any]       ):



   """simple docstring"""





   return self.tokenizer.decode(*lowerCamelCase				,   **lowerCamelCase       )






 @property
 def 		lowercase_(   self			:    List[str]       ):



   """simple docstring"""





   __A		:     int												=		self.tokenizer.model_input_names
   __A		:     Optional[Any]												=		self.feature_extractor.model_input_names
   return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names       )       )

'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__   :		int 		=logging.get_logger(__name__)

A__   :		Union[str, Any] 		={
    '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				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       ='''dpr'''
 def __init__(   self			:    Optional[int]				,   lowerCamelCase			:    Tuple=3_05_22				,   lowerCamelCase			:    List[str]=7_68				,   lowerCamelCase			:    Union[str, Any]=12				,   lowerCamelCase			:    Tuple=12				,   lowerCamelCase			:    Dict=30_72				,   lowerCamelCase			:    List[Any]="gelu"				,   lowerCamelCase			:    List[Any]=0.1				,   lowerCamelCase			:    Union[str, Any]=0.1				,   lowerCamelCase			:    Optional[Any]=5_12				,   lowerCamelCase			:    List[Any]=2				,   lowerCamelCase			:    int=0.02				,   lowerCamelCase			:    Union[str, Any]=1e-1_2				,   lowerCamelCase			:    int=0				,   lowerCamelCase			:    List[str]="absolute"				,   lowerCamelCase			:    int = 0				,   **lowerCamelCase			:    List[Any]				,   ):



   """simple docstring"""





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

   __A		:     Dict												=		vocab_size
   __A		:     int												=		hidden_size
   __A		:     str												=		num_hidden_layers
   __A		:     Union[str, Any]												=		num_attention_heads
   __A		:     Union[str, Any]												=		hidden_act
   __A		:     Optional[Any]												=		intermediate_size
   __A		:     str												=		hidden_dropout_prob
   __A		:     int												=		attention_probs_dropout_prob
   __A		:     int												=		max_position_embeddings
   __A		:     Dict												=		type_vocab_size
   __A		:     Dict												=		initializer_range
   __A		:     Union[str, Any]												=		layer_norm_eps
   __A		:     int												=		projection_dim
   __A		:     List[Any]												=		position_embedding_type



