






"""simple docstring"""
import argparse
from pathlib import Path

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

def 				snake_case      (   A__	,A__	,A__	,A__	,A__ = None	,A__ = None	,A__ = None	,):
			if config_name_or_path is None:
						UpperCAmelCase_     : Optional[int]			     =					"facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"

			if generator_tokenizer_name_or_path is None:
						UpperCAmelCase_     : str			     =					generator_name_or_path

			if question_encoder_tokenizer_name_or_path is None:
						UpperCAmelCase_     : str			     =					question_encoder_name_or_path

			UpperCAmelCase_     : int			     =					RagTokenForGeneration if model_type == "rag_token" else RagSequenceForGeneration

			# Save model.
			UpperCAmelCase_     : str			     =					RagConfig.from_pretrained(A__						)
			UpperCAmelCase_     : List[str]			     =					AutoConfig.from_pretrained(A__						)
			UpperCAmelCase_     : Tuple			     =					AutoConfig.from_pretrained(A__						)

			UpperCAmelCase_     : Optional[int]			     =					gen_config
			UpperCAmelCase_     : List[Any]			     =					question_encoder_config

			UpperCAmelCase_     : 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_     : 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__":
			lowerCamelCase_					=      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_					=      parser.parse_args()

			lowerCamelCase_					=      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"""
def 				snake_case      (   A__	,A__	,A__	,A__	,A__						):
			if index == number_of_items:
						return 0
			UpperCAmelCase_     : str			     =					0
			UpperCAmelCase_     : Dict			     =					0
			UpperCAmelCase_     : Tuple			     =					knapsack(A__	,A__	,A__	,A__	,index + 1						)
			if weights[index] <= max_weight:
						UpperCAmelCase_     : Union[str, Any]			     =					values[index] + knapsack(
						    A__	,A__	,A__	,max_weight - weights[index]	,index + 1						)
			return max(A__	,A__						)


if __name__ == "__main__":
			import doctest

			doctest.testmod()



