


'''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


lowercase							= logging.get_logger(__name__)






class  __magic_name__							:






       def __init__(      self  ,							snake_case  ,							snake_case)						->  List[Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       Union[str, Any]							   =question_encoder
          _UpperCAmelCase       :       Any							   =generator
          _UpperCAmelCase       :       Union[str, Any]							   =self.question_encoder






       def       lowerCAmelCase		(      self  ,							snake_case)						->  Dict:




          '''simple docstring'''
          if os.path.isfile(snake_case):
             raise ValueError(f"Provided path ({save_directory}) should be a directory, not a file")
          os.makedirs(snake_case  ,							exist_ok=snake_case)
          _UpperCAmelCase       :       List[Any]							   =os.path.join(snake_case  ,							'question_encoder_tokenizer')
          _UpperCAmelCase       :       List[Any]							   =os.path.join(snake_case  ,							'generator_tokenizer')
          self.question_encoder.save_pretrained(snake_case)
          self.generator.save_pretrained(snake_case)






       @classmethod
       def       lowerCAmelCase		(      cls  ,							snake_case  ,							**snake_case)						->  List[Any]:




          '''simple docstring'''
          from ..auto.tokenization_auto import AutoTokenizer

          _UpperCAmelCase       :       List[str]							   =kwargs.pop('config'  ,							snake_case)

          if config is None:
             _UpperCAmelCase       :       Optional[Any]							   =RagConfig.from_pretrained(snake_case)

          _UpperCAmelCase       :       List[str]							   =AutoTokenizer.from_pretrained(
              snake_case  ,							config=config.question_encoder  ,							subfolder='question_encoder_tokenizer')
          _UpperCAmelCase       :       Tuple							   =AutoTokenizer.from_pretrained(
              snake_case  ,							config=config.generator  ,							subfolder='generator_tokenizer')
          return cls(question_encoder=snake_case  ,							generator=snake_case)






       def __call__(      self  ,							*snake_case  ,							**snake_case)						->  Dict:




          '''simple docstring'''
          return self.current_tokenizer(*snake_case  ,							**snake_case)






       def       lowerCAmelCase		(      self  ,							*snake_case  ,							**snake_case)						->  Union[str, Any]:




          '''simple docstring'''
          return self.generator.batch_decode(*snake_case  ,							**snake_case)






       def       lowerCAmelCase		(      self  ,							*snake_case  ,							**snake_case)						->  List[str]:




          '''simple docstring'''
          return self.generator.decode(*snake_case  ,							**snake_case)






       def       lowerCAmelCase		(      self)						->  Union[str, Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       str							   =self.question_encoder






       def       lowerCAmelCase		(      self)						->  str:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[Any]							   =self.generator






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None  ,							snake_case = None  ,							snake_case = None  ,							snake_case = "longest"  ,							snake_case = None  ,							snake_case = True  ,							**snake_case  ,							)						->  BatchEncoding:




          '''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'  ,							snake_case  ,							)
          if max_length is None:
             _UpperCAmelCase       :       List[Any]							   =self.current_tokenizer.model_max_length
          _UpperCAmelCase       :       str							   =self(
              snake_case  ,							add_special_tokens=snake_case  ,							return_tensors=snake_case  ,							max_length=snake_case  ,							padding=snake_case  ,							truncation=snake_case  ,							**snake_case  ,							)
          if tgt_texts is None:
             return model_inputs
          # Process tgt_texts
          if max_target_length is None:
             _UpperCAmelCase       :       Any							   =self.current_tokenizer.model_max_length
          _UpperCAmelCase       :       List[Any]							   =self(
              text_target=snake_case  ,							add_special_tokens=snake_case  ,							return_tensors=snake_case  ,							padding=snake_case  ,							max_length=snake_case  ,							truncation=snake_case  ,							**snake_case  ,							)
          _UpperCAmelCase       :       Dict							   =labels['input_ids']
          return model_inputs





'''simple docstring'''






lowercase							=[0, 2, 4, 6, 8]
lowercase							=[1, 3, 5, 7, 9]





def lowerCamelCase__      (						__lowerCamelCase	:							int	,   __lowerCamelCase	:							int	,   __lowerCamelCase	:							list[int]	,   __lowerCamelCase	:							int							):







   '''simple docstring'''




   if remaining_length == 0:
      if digits[0] == 0 or digits[-1] == 0:
         return 0

      for i in range(length // 2 - 1	,   -1	,   -1							):
         remainder += digits[i] + digits[length - i - 1]

         if remainder % 2 == 0:
            return 0

         remainder //= 1_0

      return 1

   if remaining_length == 1:
      if remainder % 2 == 0:
         return 0

      _UpperCAmelCase       :       Union[str, Any]							   =0
      for digit in range(1_0							):
         _UpperCAmelCase       :       str							   =digit
         result += reversible_numbers(
             0	,   (remainder + 2 * digit) // 1_0	,   __lowerCamelCase	,   __lowerCamelCase							)
      return result

   _UpperCAmelCase       :       Optional[Any]							   =0
   for digita in range(1_0							):
      _UpperCAmelCase       :       Any							   =digita

      if (remainder + digita) % 2 == 0:
         _UpperCAmelCase       :       Optional[int]							   =ODD_DIGITS
      else:
         _UpperCAmelCase       :       Union[str, Any]							   =EVEN_DIGITS

      for digita in other_parity_digits:
         _UpperCAmelCase       :       int							   =digita
         result += reversible_numbers(
             remaining_length - 2	,   (remainder + digita + digita) // 1_0	,   __lowerCamelCase	,   __lowerCamelCase	,   )
   return result





def lowerCamelCase__      (						__lowerCamelCase	:							int = 9							):







   '''simple docstring'''




   _UpperCAmelCase       :       Optional[int]							   =0
   for length in range(1	,   max_power + 1							):
      result += reversible_numbers(__lowerCamelCase	,   0	,   [0] * length	,   __lowerCamelCase							)
   return result


if __name__ == "__main__":
 print(F"""{solution() = }""")

