






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     :							Optional[Any]    =logging.get_logger(__name__)


lowerCamelCase     :							Optional[Any]    ={'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCamelCase     :							List[Any]    ={
    '''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       __a  (   snake_case_	):
 _lowerCAmelCase	:	List[str]				=			VOCAB_FILES_NAMES
 _lowerCAmelCase	:	Union[str, Any]				=			PRETRAINED_VOCAB_FILES_MAP
 _lowerCAmelCase	:	Union[str, Any]				=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCAmelCase	:	Union[str, Any]				=			["input_ids", "attention_mask"]
 _lowerCAmelCase	:	Any				=			BartTokenizer







 def __init__(		self :       List[str]							,       SCREAMING_SNAKE_CASE :       Optional[int]=None							,       SCREAMING_SNAKE_CASE :       Optional[Any]=None							,       SCREAMING_SNAKE_CASE :       Tuple=None							,       SCREAMING_SNAKE_CASE :       Dict="replace"							,       SCREAMING_SNAKE_CASE :       Any="<s>"							,       SCREAMING_SNAKE_CASE :       Any="</s>"							,       SCREAMING_SNAKE_CASE :       str="</s>"							,       SCREAMING_SNAKE_CASE :       Optional[Any]="<s>"							,       SCREAMING_SNAKE_CASE :       List[str]="<unk>"							,       SCREAMING_SNAKE_CASE :       int="<pad>"							,       SCREAMING_SNAKE_CASE :       Tuple="<mask>"							,       SCREAMING_SNAKE_CASE :       List[str]=False							,       SCREAMING_SNAKE_CASE :       str=True							,       **SCREAMING_SNAKE_CASE :       Any							,       ):


      '''simple docstring'''






      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__      :       Dict	    =  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
      if pre_tok_state.get("add_prefix_space"							,       _A						) != add_prefix_space:
           UpperCamelCase__      :       Optional[Any]	    =  getattr(_A							,       pre_tok_state.pop("type"						)						)
           UpperCamelCase__      :       int	    =  add_prefix_space
           UpperCamelCase__      :       Optional[int]	    =  pre_tok_class(**_A						)

      UpperCamelCase__      :       Any	    =  add_prefix_space

      # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
      UpperCamelCase__      :       List[str]	    =  'post_processor'
      UpperCamelCase__      :       Union[str, Any]	    =  getattr(self.backend_tokenizer							,       _A							,       _A						)
      if tokenizer_component_instance:
           UpperCamelCase__      :       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:
                UpperCamelCase__      :       Union[str, Any]	    =  tuple(state["sep"]						)
           if "cls" in state:
                UpperCamelCase__      :       int	    =  tuple(state["cls"]						)

           UpperCamelCase__      :       Optional[int]	    =  False

           if state.get("add_prefix_space"							,       _A						) != add_prefix_space:
                UpperCamelCase__      :       Any	    =  add_prefix_space
                UpperCamelCase__      :       Optional[Any]	    =  True

           if state.get("trim_offsets"							,       _A						) != trim_offsets:
                UpperCamelCase__      :       Optional[int]	    =  trim_offsets
                UpperCamelCase__      :       str	    =  True

           if changes_to_apply:
                UpperCamelCase__      :       List[Any]	    =  getattr(_A							,       state.pop("type"						)						)
                UpperCamelCase__      :       Optional[int]	    =  component_class(**_A						)
                setattr(self.backend_tokenizer							,       _A							,       _A						)







 @property
 def  __lowercase (		self :       List[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 :       Optional[int]							,       SCREAMING_SNAKE_CASE :       Tuple						):


      '''simple docstring'''






      UpperCamelCase__      :       Tuple	    =  AddedToken(_A							,       lstrip=_A							,       rstrip=_A						) if isinstance(_A							,       _A						) else value
      UpperCamelCase__      :       List[str]	    =  value







 def  __lowercase (		self :       Union[str, Any]							,       *SCREAMING_SNAKE_CASE :       List[Any]							,       **SCREAMING_SNAKE_CASE :       Union[str, Any]						):


      '''simple docstring'''






      UpperCamelCase__      :       Union[str, Any]	    =  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 :       Union[str, Any]							,       *SCREAMING_SNAKE_CASE :       Optional[Any]							,       **SCREAMING_SNAKE_CASE :       str						):


      '''simple docstring'''






      UpperCamelCase__      :       List[Any]	    =  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 :       Optional[Any]							,       SCREAMING_SNAKE_CASE :       str							,       SCREAMING_SNAKE_CASE :       Optional[str] = None						):


      '''simple docstring'''






      UpperCamelCase__      :       List[str]	    =  self._tokenizer.model.save(_A							,       name=_A						)
      return tuple(_A						)







 def  __lowercase (		self :       List[Any]							,       SCREAMING_SNAKE_CASE :       int							,       SCREAMING_SNAKE_CASE :       str=None						):


      '''simple docstring'''






      UpperCamelCase__      :       int	    =  [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 :       Any							,       SCREAMING_SNAKE_CASE :       List[int]							,       SCREAMING_SNAKE_CASE :       Optional[List[int]] = None						):


      '''simple docstring'''






      UpperCamelCase__      :       List[Any]	    =  [self.sep_token_id]
      UpperCamelCase__      :       Tuple	    =  [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 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase ,   __lowerCAmelCase      )			->     Any:
     # "extended trapezoidal rule"
     # int(f) = dx/2 * (f1 + 2f2 + ... + fn)
     UpperCamelCase__      :       int	    =  (boundary[1] - boundary[0]) / steps
     UpperCamelCase__      :       Optional[Any]	    =  boundary[0]
     UpperCamelCase__      :       List[Any]	    =  boundary[1]
     UpperCamelCase__      :       List[Any]	    =  make_points(__lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase      )
     UpperCamelCase__      :       int	    =  0.0
     y += (h / 2.0) * f(__lowerCAmelCase      )
     for i in x_i:
          # print(i)
          y += h * f(__lowerCAmelCase      )
     y += (h / 2.0) * f(__lowerCAmelCase      )
     return y







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase ,   __lowerCAmelCase ,   __lowerCAmelCase      )			->     List[str]:
     UpperCamelCase__      :       Optional[int]	    =  a + h
     while x < (b - h):
          yield x
          UpperCamelCase__      :       Union[str, Any]	    =  x + h







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase      )			->     Any:  # enter your function here
     UpperCamelCase__      :       Dict	    =  (x - 0) * (x - 0)
     return y







def 		SCREAMING_SNAKE_CASE							( )			->     Dict:
     UpperCamelCase__      :       List[Any]	    =  0.0  # Lower bound of integration
     UpperCamelCase__      :       Tuple	    =  1.0  # Upper bound of integration
     UpperCamelCase__      :       Any	    =  1_0.0  # define number of steps or resolution
     UpperCamelCase__      :       List[str]	    =  [a, b]  # define boundary of integration
     UpperCamelCase__      :       Any	    =  method_a(__lowerCAmelCase ,   __lowerCAmelCase      )
     print(f'y = {y}'      )


if __name__ == "__main__":
 main()