
'''simple docstring'''





import argparse
from pathlib import Path

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







def snake_case_     (					lowercase__   ,       lowercase__   ,       lowercase__   ,       lowercase__   ,       lowercase__ = None   ,       lowercase__ = None   ,       lowercase__ = None   ,       ):
  if config_name_or_path is None:
    UpperCAmelCase__      :					Optional[Any]				       =							"facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"

  if generator_tokenizer_name_or_path is None:
    UpperCAmelCase__      :					Optional[int]				       =							generator_name_or_path

  if question_encoder_tokenizer_name_or_path is None:
    UpperCAmelCase__      :					Tuple				       =							question_encoder_name_or_path

  UpperCAmelCase__      :					Optional[int]				       =							RagTokenForGeneration if model_type == "rag_token" else RagSequenceForGeneration

  # Save model.
  UpperCAmelCase__      :					int				       =							RagConfig.from_pretrained(__A		)
  UpperCAmelCase__      :					int				       =							AutoConfig.from_pretrained(__A		)
  UpperCAmelCase__      :					List[Any]				       =							AutoConfig.from_pretrained(__A		)

  UpperCAmelCase__      :					List[Any]				       =							gen_config
  UpperCAmelCase__      :					List[Any]				       =							question_encoder_config

  UpperCAmelCase__      :					List[str]				       =							model_class.from_pretrained_question_encoder_generator(
      __A   ,       __A   ,       config=__A		)
  rag_model.save_pretrained(__A		)

  # Sanity check.
  model_class.from_pretrained(__A		)

  # Save tokenizers.
  UpperCAmelCase__      :					int				       =							AutoTokenizer.from_pretrained(__A		)
  gen_tokenizer.save_pretrained(dest_dir / "generator_tokenizer/"		)
  UpperCAmelCase__      :					Optional[int]				       =							AutoTokenizer.from_pretrained(__A		)
  question_encoder_tokenizer.save_pretrained(dest_dir / "question_encoder_tokenizer/"		)


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE     =       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``"""
          ),
      )

      SCREAMING_SNAKE_CASE     =       parser.parse_args()

      SCREAMING_SNAKE_CASE     =       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,
      )






import argparse
from pathlib import Path

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





def      A__					(			__A  :						Any     ,				__A  :						str     ,				__A  :						str     ,				__A  :						Path     ,				__A  :						str = None     ,				__A  :						str = None     ,				__A  :						str = None     ,				)					->Optional[Any]:
      if config_name_or_path is None:
            __A    ='''facebook/rag-token-base''' if model_type == '''rag_token''' else '''facebook/rag-sequence-base'''

      if generator_tokenizer_name_or_path is None:
            __A    =generator_name_or_path

      if question_encoder_tokenizer_name_or_path is None:
            __A    =question_encoder_name_or_path

      __A    =RagTokenForGeneration if model_type == '''rag_token''' else RagSequenceForGeneration

      # Save model.
      __A    =RagConfig.from_pretrained(__A			)
      __A    =AutoConfig.from_pretrained(__A			)
      __A    =AutoConfig.from_pretrained(__A			)

      __A    =gen_config
      __A    =question_encoder_config

      __A    =model_class.from_pretrained_question_encoder_generator(
          __A     ,				__A     ,				config=__A			)
      rag_model.save_pretrained(__A			)

      # Sanity check.
      model_class.from_pretrained(__A			)

      # Save tokenizers.
      __A    =AutoTokenizer.from_pretrained(__A			)
      gen_tokenizer.save_pretrained(dest_dir / '''generator_tokenizer/'''			)
      __A    =AutoTokenizer.from_pretrained(__A			)
      question_encoder_tokenizer.save_pretrained(dest_dir / '''question_encoder_tokenizer/'''			)


if __name__ == "__main__":
   _lowerCamelCase      :					List[str]					    =      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``'''
       ),
   )

   _lowerCamelCase      :					str					    =      parser.parse_args()

   _lowerCamelCase      :					Optional[int]					    =      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,
   )


