




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings


_lowerCAmelCase						:   Any		=   r"\n    [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n    can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information.\n\n    Args:\n        title_sep (`str`, *optional*, defaults to  `\" / \"`):\n            Separator inserted between the title and the text of the retrieved document when calling [`RagRetriever`].\n        doc_sep (`str`, *optional*, defaults to  `\" // \"`):\n            Separator inserted between the text of the retrieved document and the original input when calling\n            [`RagRetriever`].\n        n_docs (`int`, *optional*, defaults to 5):\n            Number of documents to retrieve.\n        max_combined_length (`int`, *optional*, defaults to 300):\n            Max length of contextualized input returned by [`~RagRetriever.__call__`].\n        retrieval_vector_size (`int`, *optional*, defaults to 768):\n            Dimensionality of the document embeddings indexed by [`RagRetriever`].\n        retrieval_batch_size (`int`, *optional*, defaults to 8):\n            Retrieval batch size, defined as the number of queries issues concurrently to the faiss index encapsulated\n            [`RagRetriever`].\n        dataset (`str`, *optional*, defaults to `\"wiki_dpr\"`):\n            A dataset identifier of the indexed dataset in HuggingFace Datasets (list all available datasets and ids\n            using `datasets.list_datasets()`).\n        dataset_split (`str`, *optional*, defaults to `\"train\"`)\n            Which split of the `dataset` to load.\n        index_name (`str`, *optional*, defaults to `\"compressed\"`)\n            The index name of the index associated with the `dataset`. One can choose between `\"legacy\"`, `\"exact\"` and\n            `\"compressed\"`.\n        index_path (`str`, *optional*)\n            The path to the serialized faiss index on disk.\n        passages_path (`str`, *optional*):\n            A path to text passages compatible with the faiss index. Required if using\n            [`~models.rag.retrieval_rag.LegacyIndex`]\n        use_dummy_dataset (`bool`, *optional*, defaults to `False`)\n            Whether to load a \"dummy\" variant of the dataset specified by `dataset`.\n        label_smoothing (`float`, *optional*, defaults to 0.0):\n            Only relevant if `return_loss` is set to `True`. Controls the `epsilon` parameter value for label smoothing\n            in the loss calculation. If set to 0, no label smoothing is performed.\n        do_marginalize (`bool`, *optional*, defaults to `False`):\n            If `True`, the logits are marginalized over all documents by making use of\n            `torch.nn.functional.log_softmax`.\n        reduce_loss (`bool`, *optional*, defaults to `False`):\n            Whether or not to reduce the NLL loss using the `torch.Tensor.sum` operation.\n        do_deduplication (`bool`, *optional*, defaults to `True`):\n            Whether or not to deduplicate the generations from different context documents for a given input. Has to be\n            set to `False` if used while training with distributed backend.\n        exclude_bos_score (`bool`, *optional*, defaults to `False`):\n            Whether or not to disregard the BOS token when computing the loss.\n        output_retrieved(`bool`, *optional*, defaults to `False`):\n            If set to `True`, `retrieved_doc_embeds`, `retrieved_doc_ids`, `context_input_ids` and\n            `context_attention_mask` are returned. See returned tensors for more detail.\n        use_cache (`bool`, *optional*, defaults to `True`):\n            Whether or not the model should return the last key/values attentions (not used by all models).\n        forced_eos_token_id (`int`, *optional*):\n            The id of the token to force as the last generated token when `max_length` is reached. Usually set to\n            `eos_token_id`.\n"
@add_start_docstrings(lowerCAmelCase		)
class 			_UpperCamelCase      (				lowerCAmelCase		):
      UpperCAmelCase_        =		"""rag"""
      UpperCAmelCase_        =		True
      def __init__(			self   :Optional[int] ,      lowerCamelCase   :Dict=None ,      lowerCamelCase   :List[str]=True ,      lowerCamelCase   :List[Any]=None ,      lowerCamelCase   :Union[str, Any]=None ,      lowerCamelCase   :List[str]=None ,      lowerCamelCase   :Any=None ,      lowerCamelCase   :Union[str, Any]=None ,      lowerCamelCase   :Union[str, Any]=" / " ,      lowerCamelCase   :Any=" // " ,      lowerCamelCase   :Dict=5 ,      lowerCamelCase   :Tuple=300 ,      lowerCamelCase   :int=768 ,      lowerCamelCase   :str=8 ,      lowerCamelCase   :Tuple="wiki_dpr" ,      lowerCamelCase   :List[str]="train" ,      lowerCamelCase   :str="compressed" ,      lowerCamelCase   :List[Any]=None ,      lowerCamelCase   :int=None ,      lowerCamelCase   :Union[str, Any]=False ,      lowerCamelCase   :Optional[Any]=False ,      lowerCamelCase   :Union[str, Any]=0.0 ,      lowerCamelCase   :Union[str, Any]=True ,      lowerCamelCase   :Optional[Any]=False ,      lowerCamelCase   :Tuple=False ,      lowerCamelCase   :Union[str, Any]=False ,      lowerCamelCase   :List[str]=True ,      lowerCamelCase   :str=None ,      **lowerCamelCase   :Optional[int] ,      )     ->			List[str]:
       super().__init__(
           bos_token_id=lowerCamelCase ,      pad_token_id=lowerCamelCase ,      eos_token_id=lowerCamelCase ,      decoder_start_token_id=lowerCamelCase ,      forced_eos_token_id=lowerCamelCase ,      is_encoder_decoder=lowerCamelCase ,      prefix=lowerCamelCase ,      vocab_size=lowerCamelCase ,      **lowerCamelCase ,      )
       assert (
           "question_encoder" in kwargs and "generator" in kwargs
       ), "Config has to be initialized with question_encoder and generator config"
       UpperCAmelCase__							 =						kwargs.pop("question_encoder"      )
       UpperCAmelCase__							 =						question_encoder_config.pop("model_type"      )
       UpperCAmelCase__							 =						kwargs.pop("generator"      )
       UpperCAmelCase__							 =						decoder_config.pop("model_type"      )

       from ..auto.configuration_auto import AutoConfig

       UpperCAmelCase__							 =						AutoConfig.for_model(lowerCamelCase ,      **lowerCamelCase      )
       UpperCAmelCase__							 =						AutoConfig.for_model(lowerCamelCase ,      **lowerCamelCase      )

       UpperCAmelCase__							 =						reduce_loss
       UpperCAmelCase__							 =						label_smoothing
       UpperCAmelCase__							 =						exclude_bos_score
       UpperCAmelCase__							 =						do_marginalize

       UpperCAmelCase__							 =						title_sep
       UpperCAmelCase__							 =						doc_sep
       UpperCAmelCase__							 =						n_docs
       UpperCAmelCase__							 =						max_combined_length

       UpperCAmelCase__							 =						dataset
       UpperCAmelCase__							 =						dataset_split
       UpperCAmelCase__							 =						index_name

       UpperCAmelCase__							 =						retrieval_vector_size
       UpperCAmelCase__							 =						retrieval_batch_size
       UpperCAmelCase__							 =						passages_path
       UpperCAmelCase__							 =						index_path
       UpperCAmelCase__							 =						use_dummy_dataset

       UpperCAmelCase__							 =						output_retrieved

       UpperCAmelCase__							 =						do_deduplication

       UpperCAmelCase__							 =						use_cache

       if self.forced_eos_token_id is None:
        UpperCAmelCase__							 =						getattr(self.generator ,      "forced_eos_token_id" ,      lowerCamelCase      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Tuple ,      lowerCamelCase   :PretrainedConfig ,      lowerCamelCase   :PretrainedConfig ,      **lowerCamelCase   :Optional[Any]      )     ->			PretrainedConfig:
       return cls(question_encoder=question_encoder_config.to_dict() ,      generator=generator_config.to_dict() ,      **lowerCamelCase      )







      def 	UpperCAmelCase_						(			self   :int      )     ->			Union[str, Any]:
       UpperCAmelCase__							 =						copy.deepcopy(self.__dict__      )
       UpperCAmelCase__							 =						self.question_encoder.to_dict()
       UpperCAmelCase__							 =						self.generator.to_dict()
       UpperCAmelCase__							 =						self.__class__.model_type
       return output











from ..utils import DummyObject, requires_backends
class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :List[Any] ,      *lowerCamelCase   :int ,      **lowerCamelCase   :List[Any]      )     ->			Dict:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Union[str, Any] ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :List[str]      )     ->			int:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[int] ,      *lowerCamelCase   :List[str] ,      **lowerCamelCase   :List[Any]      )     ->			Dict:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Dict ,      *lowerCamelCase   :int ,      **lowerCamelCase   :str      )     ->			str:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[int] ,      *lowerCamelCase   :Tuple ,      **lowerCamelCase   :List[Any]      )     ->			Optional[int]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[Any] ,      *lowerCamelCase   :Dict ,      **lowerCamelCase   :Optional[int]      )     ->			List[Any]:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :List[str] ,      *lowerCamelCase   :Union[str, Any] ,      **lowerCamelCase   :Any      )     ->			Union[str, Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[Any] ,      *lowerCamelCase   :str ,      **lowerCamelCase   :List[Any]      )     ->			Tuple:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :str ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :Dict      )     ->			int:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Union[str, Any] ,      *lowerCamelCase   :int ,      **lowerCamelCase   :Dict      )     ->			List[Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :int ,      *lowerCamelCase   :Union[str, Any] ,      **lowerCamelCase   :str      )     ->			Optional[int]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[str] ,      *lowerCamelCase   :Optional[int] ,      **lowerCamelCase   :Tuple      )     ->			Dict:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Union[str, Any] ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :List[str]      )     ->			Union[str, Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[Any] ,      *lowerCamelCase   :Union[str, Any] ,      **lowerCamelCase   :Optional[Any]      )     ->			Optional[int]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[Any] ,      *lowerCamelCase   :Dict ,      **lowerCamelCase   :Optional[int]      )     ->			List[str]:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Tuple ,      *lowerCamelCase   :str ,      **lowerCamelCase   :List[str]      )     ->			List[Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Any ,      *lowerCamelCase   :List[str] ,      **lowerCamelCase   :Any      )     ->			int:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[Any] ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :Optional[Any]      )     ->			Tuple:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Any ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :List[str]      )     ->			List[str]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[Any] ,      *lowerCamelCase   :Optional[int] ,      **lowerCamelCase   :Dict      )     ->			Union[str, Any]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :int ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :str      )     ->			str:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :str ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :Union[str, Any]      )     ->			Optional[Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[Any] ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :List[str]      )     ->			int:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[Any] ,      *lowerCamelCase   :Union[str, Any] ,      **lowerCamelCase   :Union[str, Any]      )     ->			List[Any]:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Dict ,      *lowerCamelCase   :Dict ,      **lowerCamelCase   :int      )     ->			List[Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Tuple ,      *lowerCamelCase   :Optional[Any] ,      **lowerCamelCase   :Optional[int]      )     ->			Dict:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :Any ,      *lowerCamelCase   :Optional[int] ,      **lowerCamelCase   :List[str]      )     ->			List[Any]:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :List[Any] ,      *lowerCamelCase   :int ,      **lowerCamelCase   :Optional[Any]      )     ->			List[str]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :int ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :List[Any]      )     ->			Any:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :str ,      *lowerCamelCase   :Optional[int] ,      **lowerCamelCase   :str      )     ->			List[str]:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :List[Any] ,      *lowerCamelCase   :str ,      **lowerCamelCase   :int      )     ->			List[Any]:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[str] ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :Any      )     ->			List[Any]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :Optional[Any] ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :Tuple      )     ->			int:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :Any ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :Tuple      )     ->			Dict:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :List[Any] ,      *lowerCamelCase   :int ,      **lowerCamelCase   :Union[str, Any]      )     ->			List[Any]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :str ,      *lowerCamelCase   :int ,      **lowerCamelCase   :List[str]      )     ->			List[str]:
       requires_backends(cls ,      ["flax"]      )



class 			_UpperCamelCase      (				metaclass=lowerCAmelCase		):
      UpperCAmelCase_        =		["""flax"""]
      def __init__(			self   :int ,      *lowerCamelCase   :Dict ,      **lowerCamelCase   :Optional[int]      )     ->			str:
       requires_backends(self ,      ["flax"]      )
      @classmethod
      def 	UpperCAmelCase_						(			cls   :Union[str, Any] ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :Union[str, Any]      )     ->			Optional[int]:
       requires_backends(cls ,      ["flax"]      )







      @classmethod
      def 	UpperCAmelCase_						(			cls   :int ,      *lowerCamelCase   :Union[str, Any] ,      **lowerCamelCase   :Any      )     ->			Optional[Any]:
       requires_backends(cls ,      ["flax"]      )





