

'''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


_snake_case     =  logging.get_logger(__name__)


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

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

_snake_case     =  {
    'facebook/bart-base': 1_024,
    'facebook/bart-large': 1_024,
    'facebook/bart-large-mnli': 1_024,
    'facebook/bart-large-cnn': 1_024,
    'facebook/bart-large-xsum': 1_024,
    'yjernite/bart_eli5': 1_024,
}


class    a__  (							lowerCamelCase_  ):
   _SCREAMING_SNAKE_CASE    :     Union[str, Any]	       =							VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE    :     List[Any]	       =							PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE    :     Optional[Any]	       =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE    :     List[Any]	       =							['input_ids', 'attention_mask']
   _SCREAMING_SNAKE_CASE    :     Optional[Any]	       =							BartTokenizer


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





      """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			,				)

      _lowercase			:      Any			     =   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
      if pre_tok_state.get("add_prefix_space"			,				_UpperCamelCase  ) != add_prefix_space:
         _lowercase			:      str			     =   getattr(_UpperCamelCase			,				pre_tok_state.pop("type"  )  )
         _lowercase			:      List[str]			     =   add_prefix_space
         _lowercase			:      str			     =   pre_tok_class(**_UpperCamelCase  )

      _lowercase			:      List[str]			     =   add_prefix_space

      # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
      _lowercase			:      List[Any]			     =   "post_processor"
      _lowercase			:      Optional[int]			     =   getattr(self.backend_tokenizer			,				_UpperCamelCase			,				_UpperCamelCase  )
      if tokenizer_component_instance:
         _lowercase			:      List[Any]			     =   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:
            _lowercase			:      Optional[int]			     =   tuple(state["sep"]  )
         if "cls" in state:
            _lowercase			:      Dict			     =   tuple(state["cls"]  )

         _lowercase			:      Tuple			     =   False

         if state.get("add_prefix_space"			,				_UpperCamelCase  ) != add_prefix_space:
            _lowercase			:      Tuple			     =   add_prefix_space
            _lowercase			:      List[str]			     =   True

         if state.get("trim_offsets"			,				_UpperCamelCase  ) != trim_offsets:
            _lowercase			:      Dict			     =   trim_offsets
            _lowercase			:      List[str]			     =   True

         if changes_to_apply:
            _lowercase			:      Union[str, Any]			     =   getattr(_UpperCamelCase			,				state.pop("type"  )  )
            _lowercase			:      int			     =   component_class(**_UpperCamelCase  )
            setattr(self.backend_tokenizer			,				_UpperCamelCase			,				_UpperCamelCase  )


   @property
   def 						_lowerCamelCase   ( self  ):





      """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 						_lowerCamelCase   ( self			,				_UpperCamelCase  ):





      """simple docstring"""





      _lowercase			:      Union[str, Any]			     =   AddedToken(_UpperCamelCase			,				lstrip=_UpperCamelCase			,				rstrip=_UpperCamelCase  ) if isinstance(_UpperCamelCase			,				_UpperCamelCase  ) else value
      _lowercase			:      Dict			     =   value


   def 						_lowerCamelCase   ( self			,				*_UpperCamelCase			,				**_UpperCamelCase  ):





      """simple docstring"""





      _lowercase			:      Any			     =   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 						_lowerCamelCase   ( self			,				*_UpperCamelCase			,				**_UpperCamelCase  ):





      """simple docstring"""





      _lowercase			:      Dict			     =   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 						_lowerCamelCase   ( self			,				_UpperCamelCase			,				_UpperCamelCase = None  ):





      """simple docstring"""





      _lowercase			:      Optional[Any]			     =   self._tokenizer.model.save(_UpperCamelCase			,				name=_UpperCamelCase  )
      return tuple(_UpperCamelCase  )


   def 						_lowerCamelCase   ( self			,				_UpperCamelCase			,				_UpperCamelCase=None  ):





      """simple docstring"""





      _lowercase			:      str			     =   [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 						_lowerCamelCase   ( self			,				_UpperCamelCase			,				_UpperCamelCase = None  ):





      """simple docstring"""





      _lowercase			:      Any			     =   [self.sep_token_id]
      _lowercase			:      List[Any]			     =   [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]









from __future__ import annotations
def      a      (			A__	:   list[int]     )    ->      int:





      """simple docstring"""



      if not nums:
            return 0
      _lowercase	       =nums[0]
      _lowercase	       =0
      for num in nums[1:]:
            _lowercase       ,       _lowercase	       =(
                max_excluding + num,
                max(A__      ,   A__     ),
            )
      return max(A__      ,   A__     )


if __name__ == "__main__":
  import doctest

  doctest.testmod()


