
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_longformer import LongformerTokenizer


_UpperCAmelCase    			=					logging.get_logger(__name__)

_UpperCAmelCase    			=					{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_UpperCAmelCase    			=					{
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "allenai/longformer-base-4096": (
            "https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
    },
}

_UpperCAmelCase    			=					{
    "allenai/longformer-base-4096": 4096,
    "allenai/longformer-large-4096": 4096,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4096,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4096,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4096,
}

class 		__magic_name__				( __lowercase					):


  """simple docstring"""





  _UpperCamelCase						 = VOCAB_FILES_NAMES
  _UpperCamelCase						 = PRETRAINED_VOCAB_FILES_MAP
  _UpperCamelCase						 = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _UpperCamelCase						 = ["input_ids", "attention_mask"]
  _UpperCamelCase						 = LongformerTokenizer


  def __init__(					self	,		a__=None	,		a__=None	,		a__=None	,		a__="replace"	,		a__="<s>"	,		a__="</s>"	,		a__="</s>"	,		a__="<s>"	,		a__="<unk>"	,		a__="<pad>"	,		a__="<mask>"	,		a__=False	,		a__=True	,		**a__	,		):
    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__	,		)

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

    _lowerCamelCase      =						add_prefix_space

    _lowerCamelCase      =						'''post_processor'''
    _lowerCamelCase      =						getattr(self.backend_tokenizer	,		A__	,		A__		)
    if tokenizer_component_instance:
      _lowerCamelCase      =						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:
        _lowerCamelCase      =						tuple(state['''sep''']		)
      if "cls" in state:
        _lowerCamelCase      =						tuple(state['''cls''']		)

      _lowerCamelCase      =						False

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

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

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


  @property
  def     _UpperCAmelCase  (					self		):
    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     _UpperCAmelCase  (					self	,		a__		):
    _lowerCamelCase      =						AddedToken(A__	,		lstrip=A__	,		rstrip=A__		) if isinstance(A__	,		A__		) else value
    _lowerCamelCase      =						value


  def     _UpperCAmelCase  (					self	,		*a__	,		**a__		):
    _lowerCamelCase      =						kwargs.get('''is_split_into_words'''	,		A__		)
    assert self.add_prefix_space or not is_split_into_words, (
        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     _UpperCAmelCase  (					self	,		*a__	,		**a__		):
    _lowerCamelCase      =						kwargs.get('''is_split_into_words'''	,		A__		)

    assert self.add_prefix_space or not is_split_into_words, (
        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     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):
    _lowerCamelCase      =						self._tokenizer.model.save(A__	,		name=A__		)
    return tuple(A__		)


  def     _UpperCAmelCase  (					self	,		a__	,		a__=None		):
    _lowerCamelCase      =						[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     _UpperCAmelCase  (					self	,		a__	,		a__ = None		):
    _lowerCamelCase      =						[self.sep_token_id]
    _lowerCamelCase      =						[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]







def  snake_case_(_UpperCamelCase	)				->      int:



  """simple docstring"""






  _snake_case		=				len(_UpperCamelCase	)
  _snake_case		=				[0] * length
  _snake_case		=				[[False for i in range(_UpperCamelCase	)] for j in range(_UpperCamelCase	)]
  for i, c in enumerate(_UpperCamelCase	):
    _snake_case		=				i
    for j in range(i + 1	):
      if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
        _snake_case		=				True
        _snake_case		=				min(_UpperCamelCase					,			0 if j == 0 else (cut[j - 1] + 1)	)
    _snake_case		=				mincut
  return cut[length - 1]


if __name__ == "__main__":
 __A     						=      input('''Enter the string: ''').strip()
 __A     						=      find_minimum_partitions(s)
 print(f'''Minimum number of partitions required for the \'{s}\' is {ans}''')

