




import argparse
from pathlib import Path

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

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	Tuple			,			__UpperCAmelCase						:	Optional[int]			,			__UpperCAmelCase						:	int			,			__UpperCAmelCase						:	Any			,			__UpperCAmelCase						:	List[str] = None			,			__UpperCAmelCase						:	Any = None			,			__UpperCAmelCase						:	List[str] = None			,			)					-> Union[str, Any]:
      if config_name_or_path is None:
            SCREAMING_SNAKE_CASE_							=			"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_							=			generator_name_or_path

      if question_encoder_tokenizer_name_or_path is None:
            SCREAMING_SNAKE_CASE_							=			question_encoder_name_or_path

      SCREAMING_SNAKE_CASE_							=			RagTokenForGeneration if model_type == "rag_token" else RagSequenceForGeneration

      # Save model.
      SCREAMING_SNAKE_CASE_							=			RagConfig.from_pretrained(A__							)
      SCREAMING_SNAKE_CASE_							=			AutoConfig.from_pretrained(A__							)
      SCREAMING_SNAKE_CASE_							=			AutoConfig.from_pretrained(A__							)

      SCREAMING_SNAKE_CASE_							=			gen_config
      SCREAMING_SNAKE_CASE_							=			question_encoder_config

      SCREAMING_SNAKE_CASE_							=			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.
      SCREAMING_SNAKE_CASE_							=			AutoTokenizer.from_pretrained(A__							)
      gen_tokenizer.save_pretrained(dest_dir / 'generator_tokenizer/'							)
      SCREAMING_SNAKE_CASE_							=			AutoTokenizer.from_pretrained(A__							)
      question_encoder_tokenizer.save_pretrained(dest_dir / 'question_encoder_tokenizer/'							)


if __name__ == "__main__":
   lowerCamelCase__ :   Union[str, Any]					=							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__ :   int					=							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,
   )







"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_					=      logging.get_logger(__name__)

lowerCamelCase_					=      {
    '''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-430m-pile''': '''https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-1b5-pile''': '''https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-3b-pile''': '''https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-7b-pile''': '''https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-14b-pile''': '''https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-raven-1b5''': '''https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json''',
    '''RWKV/rwkv-raven-3b''': '''https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-7b''': '''https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-14b''': '''https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json''',
}







class 			UpperCamelCase_       (__A     ):
	__magic_name__	      =				'''rwkv'''
	__magic_name__	      =				{'''max_position_embeddings''': '''context_length'''}





	def __init__(      self					: str	,	lowerCAmelCase_					: str=50_277	,	lowerCAmelCase_					: Optional[int]=1_024	,	lowerCAmelCase_					: Optional[int]=4_096	,	lowerCAmelCase_					: Union[str, Any]=32	,	lowerCAmelCase_					: List[Any]=None	,	lowerCAmelCase_					: int=None	,	lowerCAmelCase_					: List[Any]=1e-5	,	lowerCAmelCase_					: str=0	,	lowerCAmelCase_					: Tuple=0	,	lowerCAmelCase_					: int=6	,	lowerCAmelCase_					: Optional[Any]=False	,	lowerCAmelCase_					: Any=True	,	**lowerCAmelCase_					: List[Any]	,	)						->			List[str]:
				UpperCAmelCase_     : Tuple			     =					vocab_size
				UpperCAmelCase_     : List[str]			     =					context_length
				UpperCAmelCase_     : Dict			     =					hidden_size
				UpperCAmelCase_     : Optional[int]			     =					num_hidden_layers
				UpperCAmelCase_     : Optional[int]			     =					attention_hidden_size if attention_hidden_size is not None else hidden_size
				UpperCAmelCase_     : Dict			     =					intermediate_size if intermediate_size is not None else 4 * hidden_size
				UpperCAmelCase_     : Any			     =					layer_norm_epsilon
				UpperCAmelCase_     : List[Any]			     =					rescale_every
				UpperCAmelCase_     : List[str]			     =					use_cache

				UpperCAmelCase_     : List[str]			     =					bos_token_id
				UpperCAmelCase_     : Union[str, Any]			     =					eos_token_id

				super().__init__(
				    tie_word_embeddings=lowerCAmelCase_	,	bos_token_id=lowerCAmelCase_	,	eos_token_id=lowerCAmelCase_	,	**lowerCAmelCase_						)



