
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


__lowerCAmelCase			:     Any           =   logging.get_logger(__name__)


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

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

__lowerCAmelCase			:     str           =   {
    '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        UpperCAmelCase_			( _A     ):


  '''simple docstring'''







  a__           =		VOCAB_FILES_NAMES
  a__           =		PRETRAINED_VOCAB_FILES_MAP
  a__           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a__           =		["""input_ids""", """attention_mask"""]
  a__           =		BartTokenizer
  def __init__( self			: Any			,							UpperCamelCase__			: Union[str, Any]=None			,							UpperCamelCase__			: Optional[Any]=None			,							UpperCamelCase__			: List[Any]=None			,							UpperCamelCase__			: List[Any]="replace"			,							UpperCamelCase__			: Union[str, Any]="<s>"			,							UpperCamelCase__			: Optional[Any]="</s>"			,							UpperCamelCase__			: Optional[int]="</s>"			,							UpperCamelCase__			: Tuple="<s>"			,							UpperCamelCase__			: Optional[Any]="<unk>"			,							UpperCamelCase__			: Any="<pad>"			,							UpperCamelCase__			: int="<mask>"			,							UpperCamelCase__			: Any=False			,							UpperCamelCase__			: Optional[int]=True			,							**UpperCamelCase__			: str			,							)			->	Dict:







    """simple docstring"""






    super().__init__(
        UpperCamelCase__			,							UpperCamelCase__			,							tokenizer_file=UpperCamelCase__			,							errors=UpperCamelCase__			,							bos_token=UpperCamelCase__			,							eos_token=UpperCamelCase__			,							sep_token=UpperCamelCase__			,							cls_token=UpperCamelCase__			,							unk_token=UpperCamelCase__			,							pad_token=UpperCamelCase__			,							mask_token=UpperCamelCase__			,							add_prefix_space=UpperCamelCase__			,							trim_offsets=UpperCamelCase__			,							**UpperCamelCase__			,							)

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

    __magic_name__				     =       add_prefix_space

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

      __magic_name__				     =       False

      if state.get("""add_prefix_space"""			,							UpperCamelCase__    ) != add_prefix_space:
        __magic_name__				     =       add_prefix_space
        __magic_name__				     =       True

      if state.get("""trim_offsets"""			,							UpperCamelCase__    ) != trim_offsets:
        __magic_name__				     =       trim_offsets
        __magic_name__				     =       True

      if changes_to_apply:
        __magic_name__				     =       getattr(UpperCamelCase__			,							state.pop("""type"""    )    )
        __magic_name__				     =       component_class(**UpperCamelCase__    )
        setattr(self.backend_tokenizer			,							UpperCamelCase__			,							UpperCamelCase__    )
  @property
  def 							_lowercase							( self			: Tuple    )			->	str:







    """simple docstring"""






    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			: Dict			,							UpperCamelCase__			: List[Any]    )			->	Dict:







    """simple docstring"""






    __magic_name__				     =       AddedToken(UpperCamelCase__			,							lstrip=UpperCamelCase__			,							rstrip=UpperCamelCase__    ) if isinstance(UpperCamelCase__			,							UpperCamelCase__    ) else value
    __magic_name__				     =       value
  def 							_lowercase							( self			: Tuple			,							*UpperCamelCase__			: Dict			,							**UpperCamelCase__			: List[Any]    )			->	BatchEncoding:







    """simple docstring"""






    __magic_name__				     =       kwargs.get("""is_split_into_words"""			,							UpperCamelCase__    )

    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(*UpperCamelCase__			,							**UpperCamelCase__    )
  def 							_lowercase							( self			: List[Any]			,							*UpperCamelCase__			: Any			,							**UpperCamelCase__			: Optional[Any]    )			->	BatchEncoding:







    """simple docstring"""






    __magic_name__				     =       kwargs.get("""is_split_into_words"""			,							UpperCamelCase__    )

    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(*UpperCamelCase__			,							**UpperCamelCase__    )
  def 							_lowercase							( self			: List[str]			,							UpperCamelCase__			: str			,							UpperCamelCase__			: Optional[str] = None    )			->	Tuple[str]:







    """simple docstring"""






    __magic_name__				     =       self._tokenizer.model.save(UpperCamelCase__			,							name=UpperCamelCase__    )
    return tuple(UpperCamelCase__    )
  def 							_lowercase							( self			: str			,							UpperCamelCase__			: Any			,							UpperCamelCase__			: int=None    )			->	Any:







    """simple docstring"""






    __magic_name__				     =       [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]			,							UpperCamelCase__			: List[int]			,							UpperCamelCase__			: Optional[List[int]] = None    )			->	List[int]:







    """simple docstring"""






    __magic_name__				     =       [self.sep_token_id]
    __magic_name__				     =       [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"""




def        lowercase							(		lowerCAmelCase__ :     str			) ->      list:
		if n_term == "":
				return []
		__a           =			[]
		for temp in range(int(lowerCAmelCase__			)			):
				series.append(f'''1/{temp + 1}''' if series else '''1'''			)
		return series


if __name__ == "__main__":
				lowercase_			     =  input("Enter the last number (nth term) of the Harmonic Series")
				print("Formula of Harmonic Series => 1+1/2+1/3 ..... 1/n")
				print(harmonic_series(nth_term))






