






'''simple docstring'''
import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration





def  _a(  UpperCamelCase__				:						List[str],	UpperCamelCase__				:						str,	UpperCamelCase__				:						str,	UpperCamelCase__				:						Path,	UpperCamelCase__				:						str = None,	UpperCamelCase__				:						str = None,	UpperCamelCase__				:						str = None,	):




      '''simple docstring'''






      if config_name_or_path is None:
            SCREAMING_SNAKE_CASE__     :				List[Any]									='''facebook/rag-token-base''' if model_type == '''rag_token''' else '''facebook/rag-sequence-base'''

      if generator_tokenizer_name_or_path is None:
            SCREAMING_SNAKE_CASE__     :				int									=generator_name_or_path

      if question_encoder_tokenizer_name_or_path is None:
            SCREAMING_SNAKE_CASE__     :				List[str]									=question_encoder_name_or_path

      SCREAMING_SNAKE_CASE__     :				int									=RagTokenForGeneration if model_type == '''rag_token''' else RagSequenceForGeneration

      # Save model.
      SCREAMING_SNAKE_CASE__     :				Dict									=RagConfig.from_pretrained(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__     :				List[str]									=AutoConfig.from_pretrained(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__     :				List[str]									=AutoConfig.from_pretrained(UpperCamelCase__							)

      SCREAMING_SNAKE_CASE__     :				Optional[int]									=gen_config
      SCREAMING_SNAKE_CASE__     :				int									=question_encoder_config

      SCREAMING_SNAKE_CASE__     :				Optional[Any]									=model_class.from_pretrained_question_encoder_generator(
          UpperCamelCase__,	UpperCamelCase__,	config=UpperCamelCase__							)
      rag_model.save_pretrained(UpperCamelCase__							)

      # Sanity check.
      model_class.from_pretrained(UpperCamelCase__							)

      # Save tokenizers.
      SCREAMING_SNAKE_CASE__     :				List[str]									=AutoTokenizer.from_pretrained(UpperCamelCase__							)
      gen_tokenizer.save_pretrained(dest_dir / '''generator_tokenizer/'''							)
      SCREAMING_SNAKE_CASE__     :				int									=AutoTokenizer.from_pretrained(UpperCamelCase__							)
      question_encoder_tokenizer.save_pretrained(dest_dir / '''question_encoder_tokenizer/'''							)


if __name__ == "__main__":
  a_					= argparse.ArgumentParser()
  parser.add_argument(
      '--model_type',
      choices=['rag_sequence', 'rag_token'],
      required=True,
      type=str,
      help='RAG model type: rag_sequence, rag_token',
  )
  parser.add_argument('--dest', type=str, required=True, help='Path to the output checkpoint directory.')
  parser.add_argument('--generator_name_or_path', type=str, required=True, help='Generator model identifier')
  parser.add_argument(
      '--question_encoder_name_or_path', type=str, required=True, help='Question encoder model identifier'
  )

  parser.add_argument(
      '--generator_tokenizer_name_or_path',
      type=str,
      help='Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``',
  )
  parser.add_argument(
      '--question_encoder_tokenizer_name_or_path',
      type=str,
      help='Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``',
  )
  parser.add_argument(
      '--config_name_or_path',
      type=str,
      help=(
          'Identifier of the model config to use, if not provided, resolves to a base config for a given'
          ' ``model_type``'
      ),
  )

  a_					= parser.parse_args()

  a_					= Path(args.dest)
  dest_dir.mkdir(exist_ok=True)

  consolidate(
      args.model_type,
      args.generator_name_or_path,
      args.question_encoder_name_or_path,
      dest_dir,
      args.config_name_or_path,
      args.generator_tokenizer_name_or_path,
      args.question_encoder_tokenizer_name_or_path,
  )







'''simple docstring'''
class      __SCREAMING_SNAKE_CASE      :




 def __init__(      self	:							List[Any]					,      __lowercase	:							int      )	->						None:
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=size
       SCREAMING_SNAKE_CASE__     :				List[Any]									=[0] * size
       SCREAMING_SNAKE_CASE__     :				str									=[0] * size




 @staticmethod
 def      __magic_name__	(      __lowercase	:							int      )	->						int:
       return index | (index + 1)




 @staticmethod
 def      __magic_name__	(      __lowercase	:							int      )	->						int:
       return (index & (index + 1)) - 1




 def      __magic_name__	(      self	:							Dict					,      __lowercase	:							int					,      __lowercase	:							int      )	->						None:
       SCREAMING_SNAKE_CASE__     :				List[str]									=value
       while index < self.size:
             SCREAMING_SNAKE_CASE__     :				Any									=self.get_prev(__lowercase      ) + 1
             if current_left_border == index:
                   SCREAMING_SNAKE_CASE__     :				List[str]									=value
             else:
                   SCREAMING_SNAKE_CASE__     :				str									=max(__lowercase					,      __lowercase					,      __lowercase      )
             SCREAMING_SNAKE_CASE__     :				Optional[Any]									=self.get_next(__lowercase      )




 def      __magic_name__	(      self	:							Optional[int]					,      __lowercase	:							int					,      __lowercase	:							int      )	->						int:
       right -= 1  # Because of right is exclusive
       SCREAMING_SNAKE_CASE__     :				str									=0
       while left <= right:
             SCREAMING_SNAKE_CASE__     :				Optional[Any]									=self.get_prev(__lowercase      )
             if left <= current_left:
                   SCREAMING_SNAKE_CASE__     :				List[Any]									=max(__lowercase					,      self.tree[right]      )
                   SCREAMING_SNAKE_CASE__     :				Any									=current_left
             else:
                   SCREAMING_SNAKE_CASE__     :				Optional[Any]									=max(__lowercase					,      self.arr[right]      )
                   right -= 1
       return result


if __name__ == "__main__":
  import doctest

  doctest.testmod()