

'''simple docstring'''






import argparse
from pathlib import Path

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


def 	_A  (					A__  ,       A__  ,       A__  ,       A__  ,       A__ = None  ,       A__ = None  ,       A__ = None  ,       ):






 """simple docstring"""



 if config_name_or_path is None:
  __lowercase													=				'''facebook/rag-token-base''' if model_type == '''rag_token''' else '''facebook/rag-sequence-base'''

 if generator_tokenizer_name_or_path is None:
  __lowercase													=				generator_name_or_path

 if question_encoder_tokenizer_name_or_path is None:
  __lowercase													=				question_encoder_name_or_path

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

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

 __lowercase													=				gen_config
 __lowercase													=				question_encoder_config

 __lowercase													=				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.
 __lowercase													=				AutoTokenizer.from_pretrained(A__   )
 gen_tokenizer.save_pretrained(dest_dir / '''generator_tokenizer/'''   )
 __lowercase													=				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 	_A  (					A__   ):






 """simple docstring"""



 if not nums:  # Makes sure that the list is not empty
  raise ValueError('''List is empty'''   )

 __lowercase													=				sum(A__   ) / len(A__   )  # Calculate the average
 return sum(abs(x - average   ) for x in nums   ) / len(A__   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()

