



import argparse
from pathlib import Path

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






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Optional[Any] ,lowerCamelCase_	:	str ,lowerCamelCase_	:	str ,lowerCamelCase_	:	Path ,lowerCamelCase_	:	str = None ,lowerCamelCase_	:	str = None ,lowerCamelCase_	:	str = None ,):





				'''simple docstring'''

				if config_name_or_path is None:
								lowerCAmelCase__  :       Union[str, Any]				=  '''facebook/rag-token-base''' if model_type == '''rag_token''' else '''facebook/rag-sequence-base'''

				if generator_tokenizer_name_or_path is None:
								lowerCAmelCase__  :       str				=  generator_name_or_path

				if question_encoder_tokenizer_name_or_path is None:
								lowerCAmelCase__  :       List[Any]				=  question_encoder_name_or_path

				lowerCAmelCase__  :       Dict				=  RagTokenForGeneration if model_type == '''rag_token''' else RagSequenceForGeneration

				# Save model.
				lowerCAmelCase__  :       str				=  RagConfig.from_pretrained(lowerCamelCase_)
				lowerCAmelCase__  :       Optional[int]				=  AutoConfig.from_pretrained(lowerCamelCase_)
				lowerCAmelCase__  :       List[Any]				=  AutoConfig.from_pretrained(lowerCamelCase_)

				lowerCAmelCase__  :       Tuple				=  gen_config
				lowerCAmelCase__  :       Dict				=  question_encoder_config

				lowerCAmelCase__  :       str				=  model_class.from_pretrained_question_encoder_generator(
				    lowerCamelCase_ ,lowerCamelCase_ ,config=lowerCamelCase_)
				rag_model.save_pretrained(lowerCamelCase_)

				# Sanity check.
				model_class.from_pretrained(lowerCamelCase_)

				# Save tokenizers.
				lowerCAmelCase__  :       Optional[Any]				=  AutoTokenizer.from_pretrained(lowerCamelCase_)
				gen_tokenizer.save_pretrained(dest_dir / '''generator_tokenizer/''')
				lowerCAmelCase__  :       str				=  AutoTokenizer.from_pretrained(lowerCamelCase_)
				question_encoder_tokenizer.save_pretrained(dest_dir / '''question_encoder_tokenizer/''')


if __name__ == "__main__":
							__snake_case       :	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``'
							    ),
							)

							__snake_case       :	List[str]            =parser.parse_args()

							__snake_case       :	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,
							)






from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

__snake_case       :	Optional[int]            =(3, 9, -1_1, 0, 7, 5, 1, -1)
__snake_case       :	str            =(4, 6, 2, 0, 8, 1_0, 3, -2)



@dataclass
class  lowerCamelCase__    :




		'''simple docstring'''



		snake_case_			=42
		snake_case_			=42



class  lowerCamelCase__    :




		'''simple docstring'''



		def __init__(self	,__lowerCamelCase				)  ->    None:

						"""simple docstring"""






						lowerCAmelCase__  :       Node | None				=  None
						for i in sorted(__lowerCamelCase	,reverse=__lowerCamelCase				):
										lowerCAmelCase__  :       Dict				=  Node(__lowerCamelCase	,self.head				)



		def __iter__(self				)  ->    Iterator[int]:

						"""simple docstring"""






						lowerCAmelCase__  :       Optional[Any]				=  self.head
						while node:
										yield node.data
										lowerCAmelCase__  :       Dict				=  node.next_node



		def __len__(self				)  ->    int:

						"""simple docstring"""






						return sum(1 for _ in self				)



		def __str__(self				)  ->    str:

						"""simple docstring"""






						return " -> ".join([str(__lowerCamelCase				) for node in self]				)






def 			lowerCAmelCase__	(					lowerCamelCase_	:	SortedLinkedList ,lowerCamelCase_	:	SortedLinkedList):





				'''simple docstring'''

				return SortedLinkedList(list(lowerCamelCase_) + list(lowerCamelCase_))


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							__snake_case       :	Any            =SortedLinkedList
							print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))

