
"""simple docstring"""



import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


UpperCAmelCase__          = logging.get_logger(__name__)


UpperCAmelCase__          = {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all BART models at https://huggingface.co/models?filter=bart
UpperCAmelCase__          = {
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

UpperCAmelCase__          = {
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}

class       lowerCAmelCase__				(						A_	):
     __a						=					VOCAB_FILES_NAMES
     __a						=					PRETRAINED_VOCAB_FILES_MAP
     __a						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __a						=					["""input_ids""", """attention_mask"""]
     __a						=					BartTokenizer







     def __init__(							self			:			Optional[int]    ,      _lowerCamelCase			:			str=None    ,      _lowerCamelCase			:			int=None    ,      _lowerCamelCase			:			List[Any]=None    ,      _lowerCamelCase			:			List[str]="replace"    ,      _lowerCamelCase			:			Any="<s>"    ,      _lowerCamelCase			:			Union[str, Any]="</s>"    ,      _lowerCamelCase			:			str="</s>"    ,      _lowerCamelCase			:			Tuple="<s>"    ,      _lowerCamelCase			:			Any="<unk>"    ,      _lowerCamelCase			:			Optional[int]="<pad>"    ,      _lowerCamelCase			:			List[Any]="<mask>"    ,      _lowerCamelCase			:			Any=False    ,      _lowerCamelCase			:			int=True    ,      **_lowerCamelCase			:			Tuple    ,      ):
       super().__init__(
           _lowerCamelCase    ,      _lowerCamelCase    ,      tokenizer_file=_lowerCamelCase    ,      errors=_lowerCamelCase    ,      bos_token=_lowerCamelCase    ,      eos_token=_lowerCamelCase    ,      sep_token=_lowerCamelCase    ,      cls_token=_lowerCamelCase    ,      unk_token=_lowerCamelCase    ,      pad_token=_lowerCamelCase    ,      mask_token=_lowerCamelCase    ,      add_prefix_space=_lowerCamelCase    ,      trim_offsets=_lowerCamelCase    ,      **_lowerCamelCase    ,      )

       _snake_case					     =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
       if pre_tok_state.get('''add_prefix_space'''    ,      _lowerCamelCase			) != add_prefix_space:
         _snake_case					     =       getattr(_lowerCamelCase    ,      pre_tok_state.pop('''type'''			)			)
         _snake_case					     =       add_prefix_space
         _snake_case					     =       pre_tok_class(**_lowerCamelCase			)

       _snake_case					     =       add_prefix_space

       # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
       _snake_case					     =       '''post_processor'''
       _snake_case					     =       getattr(self.backend_tokenizer    ,      _lowerCamelCase    ,      _lowerCamelCase			)
       if tokenizer_component_instance:
         _snake_case					     =       json.loads(tokenizer_component_instance.__getstate__()			)

         # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
         if "sep" in state:
           _snake_case					     =       tuple(state['''sep''']			)
         if "cls" in state:
           _snake_case					     =       tuple(state['''cls''']			)

         _snake_case					     =       False

         if state.get('''add_prefix_space'''    ,      _lowerCamelCase			) != add_prefix_space:
           _snake_case					     =       add_prefix_space
           _snake_case					     =       True

         if state.get('''trim_offsets'''    ,      _lowerCamelCase			) != trim_offsets:
           _snake_case					     =       trim_offsets
           _snake_case					     =       True

         if changes_to_apply:
           _snake_case					     =       getattr(_lowerCamelCase    ,      state.pop('''type'''			)			)
           _snake_case					     =       component_class(**_lowerCamelCase			)
           setattr(self.backend_tokenizer    ,      _lowerCamelCase    ,      _lowerCamelCase			)







     @property
     def      lowercase	(							self			:			Union[str, Any]			):
       if self._mask_token is None:
         if self.verbose:
           logger.error('''Using mask_token, but it is not set yet.'''			)
         return None
       return str(self._mask_token			)







     @mask_token.setter
     def      lowercase	(							self			:			Optional[Any]    ,      _lowerCamelCase			:			List[Any]			):
       _snake_case					     =       AddedToken(_lowerCamelCase    ,      lstrip=_lowerCamelCase    ,      rstrip=_lowerCamelCase			) if isinstance(_lowerCamelCase    ,      _lowerCamelCase			) else value
       _snake_case					     =       value







     def      lowercase	(							self			:			Optional[int]    ,      *_lowerCamelCase			:			str    ,      **_lowerCamelCase			:			int			):
       _snake_case					     =       kwargs.get('''is_split_into_words'''    ,      _lowerCamelCase			)

       if is_split_into_words and not self.add_prefix_space:
         raise ValueError(
             f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
             '''to use it with pretokenized inputs.'''			)

       return super()._batch_encode_plus(*_lowerCamelCase    ,      **_lowerCamelCase			)







     def      lowercase	(							self			:			Any    ,      *_lowerCamelCase			:			Tuple    ,      **_lowerCamelCase			:			List[str]			):
       _snake_case					     =       kwargs.get('''is_split_into_words'''    ,      _lowerCamelCase			)

       if is_split_into_words and not self.add_prefix_space:
         raise ValueError(
             f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
             '''to use it with pretokenized inputs.'''			)

       return super()._encode_plus(*_lowerCamelCase    ,      **_lowerCamelCase			)







     def      lowercase	(							self			:			List[Any]    ,      _lowerCamelCase			:			str    ,      _lowerCamelCase			:			Optional[str] = None			):
       _snake_case					     =       self._tokenizer.model.save(_lowerCamelCase    ,      name=_lowerCamelCase			)
       return tuple(_lowerCamelCase			)







     def      lowercase	(							self			:			Optional[int]    ,      _lowerCamelCase			:			str    ,      _lowerCamelCase			:			Dict=None			):
       _snake_case					     =       [self.bos_token_id] + token_ids_a + [self.eos_token_id]
       if token_ids_a is None:
         return output

       return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







     def      lowercase	(							self			:			List[Any]    ,      _lowerCamelCase			:			List[int]    ,      _lowerCamelCase			:			Optional[List[int]] = None			):
       _snake_case					     =       [self.sep_token_id]
       _snake_case					     =       [self.cls_token_id]

       if token_ids_a is None:
         return len(cls + token_ids_a + sep			) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep			) * [0]





"""simple docstring"""



from math import pow
def 					_UpperCAmelCase      ( __lowerCamelCase   :       int ,					__lowerCamelCase   :       int ,					__lowerCamelCase   :       int ,					__lowerCamelCase   :       int ,					__lowerCamelCase   :       int ,					)     ->					tuple[int, int]:
  if current_sum == needed_sum:
    # If the sum of the powers is equal to needed_sum, then we have a solution.
    solutions_count += 1
    return current_sum, solutions_count

  _snake_case					     =       int(pow(__lowerCamelCase ,					__lowerCamelCase		)		)
  if current_sum + i_to_n <= needed_sum:
    # If the sum of the powers is less than needed_sum, then continue adding powers.
    current_sum += i_to_n
    _snake_case     ,					_snake_case					     =       backtrack(
        __lowerCamelCase ,					__lowerCamelCase ,					current_number + 1 ,					__lowerCamelCase ,					__lowerCamelCase		)
    current_sum -= i_to_n
  if i_to_n < needed_sum:
    # If the power of i is less than needed_sum, then try with the next power.
    _snake_case     ,					_snake_case					     =       backtrack(
        __lowerCamelCase ,					__lowerCamelCase ,					current_number + 1 ,					__lowerCamelCase ,					__lowerCamelCase		)
  return current_sum, solutions_count
def 					_UpperCAmelCase      ( __lowerCamelCase   :       int ,					__lowerCamelCase   :       int		)     ->					int:
  if not (1 <= needed_sum <= 10_00 and 2 <= power <= 10):
    raise ValueError(
        '''Invalid input\n'''
        '''needed_sum must be between 1 and 1000, power between 2 and 10.'''		)

  return backtrack(__lowerCamelCase ,					__lowerCamelCase ,					1 ,					0 ,					0		)[1]  # Return the solutions_count


if __name__ == "__main__":
 import doctest

 doctest.testmod()



