'''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


SCREAMING_SNAKE_CASE_:     Any  =logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_:     Union[str, Any]  ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE_:     str  ={
    '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',
    },
}

SCREAMING_SNAKE_CASE_:     int  ={
    'facebook/bart-base': 10_24,
    'facebook/bart-large': 10_24,
    'facebook/bart-large-mnli': 10_24,
    'facebook/bart-large-cnn': 10_24,
    'facebook/bart-large-xsum': 10_24,
    'yjernite/bart_eli5': 10_24,
}




class        __A      ( UpperCamelCase__	):
    a__       :						Dict          =  VOCAB_FILES_NAMES
    a__       :						Any          =  PRETRAINED_VOCAB_FILES_MAP
    a__       :						Union[str, Any]          =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__       :						int          =  ["""input_ids""", """attention_mask"""]
    a__       :						str          =  BartTokenizer



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

         UpperCAmelCase_           =   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
         if pre_tok_state.get("add_prefix_space"   ,			__a ) != add_prefix_space:
              UpperCAmelCase_           =   getattr(__a   ,			pre_tok_state.pop("type" ) )
              UpperCAmelCase_           =   add_prefix_space
              UpperCAmelCase_           =   pre_tok_class(**__a )

         UpperCAmelCase_           =   add_prefix_space

         # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
         UpperCAmelCase_           =   "post_processor"
         UpperCAmelCase_           =   getattr(self.backend_tokenizer   ,			__a   ,			__a )
         if tokenizer_component_instance:
              UpperCAmelCase_           =   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:
                   UpperCAmelCase_           =   tuple(state["sep"] )
              if "cls" in state:
                   UpperCAmelCase_           =   tuple(state["cls"] )

              UpperCAmelCase_           =   False

              if state.get("add_prefix_space"   ,			__a ) != add_prefix_space:
                   UpperCAmelCase_           =   add_prefix_space
                   UpperCAmelCase_           =   True

              if state.get("trim_offsets"   ,			__a ) != trim_offsets:
                   UpperCAmelCase_           =   trim_offsets
                   UpperCAmelCase_           =   True

              if changes_to_apply:
                   UpperCAmelCase_           =   getattr(__a   ,			state.pop("type" ) )
                   UpperCAmelCase_           =   component_class(**__a )
                   setattr(self.backend_tokenizer   ,			__a   ,			__a )



    @property
    def 					_lowercase						(self    :    Dict ):
         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[int]   ,			__a    :    List[Any] ):
         UpperCAmelCase_           =   AddedToken(__a   ,			lstrip=__a   ,			rstrip=__a ) if isinstance(__a   ,			__a ) else value
         UpperCAmelCase_           =   value



    def 					_lowercase						(self    :    Any   ,			*__a    :    List[Any]   ,			**__a    :    Any ):
         UpperCAmelCase_           =   kwargs.get("is_split_into_words"   ,			__a )

         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(*__a   ,			**__a )



    def 					_lowercase						(self    :    List[str]   ,			*__a    :    Optional[Any]   ,			**__a    :    Dict ):
         UpperCAmelCase_           =   kwargs.get("is_split_into_words"   ,			__a )

         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(*__a   ,			**__a )



    def 					_lowercase						(self    :    str   ,			__a    :    str   ,			__a    :    Optional[str] = None ):
         UpperCAmelCase_           =   self._tokenizer.model.save(__a   ,			name=__a )
         return tuple(__a )



    def 					_lowercase						(self    :    Any   ,			__a    :    Optional[int]   ,			__a    :    str=None ):
         UpperCAmelCase_           =   [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    :    Union[str, Any]   ,			__a    :    List[int]   ,			__a    :    Optional[List[int]] = None ):
         UpperCAmelCase_           =   [self.sep_token_id]
         UpperCAmelCase_           =   [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 	a			( lowerCamelCase__						,      lowerCamelCase__						,      lowerCamelCase__						,      lowerCamelCase__						,      lowerCamelCase__						,      ):
			'''simple docstring'''





			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

			A_	:						Optional[int]	=     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
						A_,    A_	:						int	=     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.
						A_,    A_	:						int	=     backtrack(
						    lowerCamelCase__						,      lowerCamelCase__						,      current_number + 1						,      lowerCamelCase__						,      lowerCamelCase__    )
			return current_sum, solutions_count



def 	a			( lowerCamelCase__						,      lowerCamelCase__    ):
			'''simple docstring'''





			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()