






'''simple docstring'''

import argparse
from pathlib import Path

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



def 							snake_case					(     a_							: List[str]    ,   a_							: str    ,   a_							: str    ,   a_							: Path    ,   a_							: str = None    ,   a_							: str = None    ,   a_							: str = None    ,   )       ->				Any:





      """simple docstring"""

      if config_name_or_path is None:
            UpperCamelCase_				:   List[str]					    =							"facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"

      if generator_tokenizer_name_or_path is None:
            UpperCamelCase_				:   List[Any]					    =							generator_name_or_path

      if question_encoder_tokenizer_name_or_path is None:
            UpperCamelCase_				:   Optional[Any]					    =							question_encoder_name_or_path

      UpperCamelCase_				:   Optional[Any]					    =							RagTokenForGeneration if model_type == "rag_token" else RagSequenceForGeneration

      # Save model.
      UpperCamelCase_				:   str					    =							RagConfig.from_pretrained(_A	)
      UpperCamelCase_				:   Tuple					    =							AutoConfig.from_pretrained(_A	)
      UpperCamelCase_				:   Tuple					    =							AutoConfig.from_pretrained(_A	)

      UpperCamelCase_				:   Dict					    =							gen_config
      UpperCamelCase_				:   Dict					    =							question_encoder_config

      UpperCamelCase_				:   List[Any]					    =							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_				:   Any					    =							AutoTokenizer.from_pretrained(_A	)
      gen_tokenizer.save_pretrained(dest_dir / """generator_tokenizer/"""	)
      UpperCamelCase_				:   List[str]					    =							AutoTokenizer.from_pretrained(_A	)
      question_encoder_tokenizer.save_pretrained(dest_dir / """question_encoder_tokenizer/"""	)


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

  UpperCamelCase							=parser.parse_args()

  UpperCamelCase							=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'''

import warnings

from .generation import TFGenerationMixin




class     A    (      SCREAMING_SNAKE_CASE__						):






 """simple docstring"""





 warnings.warn(
     '''Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '''
     '''be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead.''',   SCREAMING_SNAKE_CASE__,   )






