

"""simple docstring"""






import os
import warnings
from typing import List, Optional

from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig


_lowerCAmelCase						=		logging.get_logger(__name__)







class 	__UpperCamelCase    :

  def __init__(		self    ,_A    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Union[str, Any]  =    question_encoder
      _lowerCAmelCase       :   List[str]  =    generator
      _lowerCAmelCase       :   str  =    self.question_encoder

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      if os.path.isfile(_A      ):
          raise ValueError(F"""Provided path ({save_directory}) should be a directory, not a file"""      )
      os.makedirs(_A    ,exist_ok=_A      )
      _lowerCAmelCase       :   Union[str, Any]  =    os.path.join(_A    ,'question_encoder_tokenizer'      )
      _lowerCAmelCase       :   Union[str, Any]  =    os.path.join(_A    ,'generator_tokenizer'      )
      self.question_encoder.save_pretrained(_A      )
      self.generator.save_pretrained(_A      )

  @classmethod
  def __lowerCamelCase		(		cls    ,_A    ,**_A      ):
      '''simple docstring'''

      from ..auto.tokenization_auto import AutoTokenizer

      _lowerCAmelCase       :   Any  =    kwargs.pop('config'    ,_A      )

      if config is None:
          _lowerCAmelCase       :   Dict  =    RagConfig.from_pretrained(_A      )

      _lowerCAmelCase       :   Optional[int]  =    AutoTokenizer.from_pretrained(
          _A    ,config=config.question_encoder    ,subfolder='question_encoder_tokenizer'      )
      _lowerCAmelCase       :   Any  =    AutoTokenizer.from_pretrained(
          _A    ,config=config.generator    ,subfolder='generator_tokenizer'      )
      return cls(question_encoder=_A    ,generator=_A      )

  def __call__(		self    ,*_A    ,**_A      ):
      '''simple docstring'''

      return self.current_tokenizer(*_A    ,**_A      )

  def __lowerCamelCase		(		self    ,*_A    ,**_A      ):
      '''simple docstring'''

      return self.generator.batch_decode(*_A    ,**_A      )

  def __lowerCamelCase		(		self    ,*_A    ,**_A      ):
      '''simple docstring'''

      return self.generator.decode(*_A    ,**_A      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[str]  =    self.question_encoder

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   int  =    self.generator







  def __lowerCamelCase		(		self    ,_A    ,_A = None    ,_A = None    ,_A = None    ,_A = "longest"    ,_A = None    ,_A = True    ,**_A    ,):
      '''simple docstring'''

      warnings.warn(
          '`prepare_seq2seq_batch` is deprecated and will be removed in version 5 of 🤗 Transformers. Use the '
          'regular `__call__` method to prepare your inputs and the tokenizer under the `with_target_tokenizer` '
          'context manager to prepare your targets. See the documentation of your specific tokenizer for more '
          'details'    ,_A    ,)
      if max_length is None:
          _lowerCAmelCase       :   Union[str, Any]  =    self.current_tokenizer.model_max_length
      _lowerCAmelCase       :   Optional[int]  =    self(
          _A    ,add_special_tokens=_A    ,return_tensors=_A    ,max_length=_A    ,padding=_A    ,truncation=_A    ,**_A    ,)
      if tgt_texts is None:
          return model_inputs
      # Process tgt_texts
      if max_target_length is None:
          _lowerCAmelCase       :   Optional[Any]  =    self.current_tokenizer.model_max_length
      _lowerCAmelCase       :   str  =    self(
          text_target=_A    ,add_special_tokens=_A    ,return_tensors=_A    ,padding=_A    ,max_length=_A    ,truncation=_A    ,**_A    ,)
      _lowerCAmelCase       :   Dict  =    labels['input_ids']
      return model_inputs








"""simple docstring"""






import baseaa

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    return baseaa.aaaencode(string.encode('utf-8'   )   )

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    return baseaa.aaadecode(_lowerCamelCase   ).decode('utf-8'   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()





