
'''simple docstring'''







import logging
import random

import ray

from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex


_lowercase :  Any    							=       logging.getLogger(__name__)






class  lowerCAmelCase__   :






					def __init__(   self		):


											"""simple docstring"""





											lowercase_	:     Any													=       False






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											if not self.initialized:
																	lowercase_	:     Union[str, Any]													=       RagRetriever(
																	    __snake_case				,							question_encoder_tokenizer=__snake_case				,							generator_tokenizer=__snake_case				,							index=__snake_case				,							init_retrieval=__snake_case				,							)
																	lowercase_	:     int													=       True






					def 	_snake_case    (   self		):


											"""simple docstring"""





											self.retriever.index.init_index()






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_						, lowercase_	:     Union[str, Any]													=       self.retriever._main_retrieve(__snake_case				,							__snake_case		)
											return doc_ids, retrieved_doc_embeds







class  lowerCAmelCase__   (  lowerCamelCase_     ):






					def __init__(   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE=None		):


											"""simple docstring"""





											if index is not None and index.is_initialized() and len(__snake_case		) > 0:
																	raise ValueError(
																	    '''When using Ray for distributed fine-tuning, '''
																	    '''you\'ll need to provide the paths instead, '''
																	    '''as the dataset and the index are loaded '''
																	    '''separately. More info in examples/rag/use_own_knowledge_dataset.py '''		)
											super().__init__(
											    __snake_case				,							question_encoder_tokenizer=__snake_case				,							generator_tokenizer=__snake_case				,							index=__snake_case				,							init_retrieval=__snake_case				,							)
											lowercase_	:     Any													=       retrieval_workers
											if len(self.retrieval_workers		) > 0:
																	ray.get(
																	    [
																	        worker.create_rag_retriever.remote(__snake_case				,							__snake_case				,							__snake_case				,							__snake_case		)
																	        for worker in self.retrieval_workers
																	    ]		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											logger.info('''initializing retrieval'''		)

											if len(self.retrieval_workers		) > 0:
																	ray.get([worker.init_retrieval.remote() for worker in self.retrieval_workers]		)
											else:
																	# Non-distributed training. Load index into this same process.
																	self.index.init_index()






					def 	_snake_case    (   self				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											if len(self.retrieval_workers		) > 0:
																	# Select a random retrieval actor.
																	lowercase_	:     str													=       self.retrieval_workers[random.randint(0				,							len(self.retrieval_workers		) - 1		)]
																	lowercase_						, lowercase_	:     Optional[Any]													=       ray.get(random_worker.retrieve.remote(__snake_case				,							__snake_case		)		)
											else:
																	lowercase_						, lowercase_	:     Optional[Any]													=       self._main_retrieve(__snake_case				,							__snake_case		)
											return retrieved_doc_embeds, doc_ids, self.index.get_doc_dicts(__snake_case		)






					@classmethod
					def 	_snake_case    (   cls				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE=None				,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return super(__snake_case				,							cls		).get_tokenizers(__snake_case				,							__snake_case				,							**__snake_case		)






					@classmethod
					def 	_snake_case    (   cls				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE=None				,							**__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_	:     Union[str, Any]													=       kwargs.pop('''config'''				,							__snake_case		) or RagConfig.from_pretrained(__snake_case				,							**__snake_case		)
											lowercase_	:     List[str]													=       RagTokenizer.from_pretrained(__snake_case				,							config=__snake_case		)
											lowercase_	:     List[str]													=       rag_tokenizer.question_encoder
											lowercase_	:     int													=       rag_tokenizer.generator
											if indexed_dataset is not None:
																	lowercase_	:     int													=       '''custom'''
																	lowercase_	:     str													=       CustomHFIndex(config.retrieval_vector_size				,							__snake_case		)
											else:
																	lowercase_	:     Optional[Any]													=       cls._build_index(__snake_case		)
											return cls(
											    __snake_case				,							question_encoder_tokenizer=__snake_case				,							generator_tokenizer=__snake_case				,							retrieval_workers=__snake_case				,							index=__snake_case				,							)







from abc import ABC, abstractmethod
from argparse import ArgumentParser







class        snake_case_   (lowerCamelCase_      ):
					@staticmethod
					@abstractmethod
					def  lowerCamelCase__(      __snake_case   :ArgumentParser      )					->    Dict:
												raise NotImplementedError()



					@abstractmethod
					def  lowerCamelCase__(      self   :Union[str, Any]      )					->    Dict:
												raise NotImplementedError()




