"""simple docstring"""







import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE  :		int        =      logging.get_logger(__name__)

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

_SCREAMING_SNAKE_CASE  :		int        =      {
    '''vocab_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/vocab.json''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/vocab.json''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/vocab.json''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/merges.txt''',
        '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/merges.txt''',
        '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt''',
        '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/merges.txt''',
        '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt''',
        '''roberta-large-openai-detector''': (
            '''https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'''
        ),
    },
}

_SCREAMING_SNAKE_CASE  :		Dict        =      {
    '''roberta-base''': 5_1_2,
    '''roberta-large''': 5_1_2,
    '''roberta-large-mnli''': 5_1_2,
    '''distilroberta-base''': 5_1_2,
    '''roberta-base-openai-detector''': 5_1_2,
    '''roberta-large-openai-detector''': 5_1_2,
}



@lru_cache()
def 			A__						(  )     ->       Any:

   '''simple docstring'''





   __lowerCamelCase								=				(
       list(range(ord('!'	)			,   ord('~'	) + 1	)	) + list(range(ord('¡'	)			,   ord('¬'	) + 1	)	) + list(range(ord('®'	)			,   ord('ÿ'	) + 1	)	)
   )
   __lowerCamelCase								=				bs[:]
   __lowerCamelCase								=				0
   for b in range(2**8	):
      if b not in bs:
         bs.append(lowercase_	)
         cs.append(2**8 + n	)
         n += 1
   __lowerCamelCase								=				[chr(lowercase_	) for n in cs]
   return dict(zip(lowercase_			,   lowercase_	)	)



def 			A__						(  lowercase_    :  Optional[Any]	)     ->       Tuple:

   '''simple docstring'''





   __lowerCamelCase								=				set()
   __lowerCamelCase								=				word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)	)
      __lowerCamelCase								=				char
   return pairs






class     _SCREAMING_SNAKE_CASE       ( UpperCAmelCase							):



   '''simple docstring'''



   __UpperCAmelCase  :       Optional[int]						=						VOCAB_FILES_NAMES
   __UpperCAmelCase  :       Tuple						=						PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase  :       Dict						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase  :       str						=						["input_ids", "attention_mask"]







   def __init__(  self   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE="replace"   ,							_SCREAMING_SNAKE_CASE="<s>"   ,							_SCREAMING_SNAKE_CASE="</s>"   ,							_SCREAMING_SNAKE_CASE="</s>"   ,							_SCREAMING_SNAKE_CASE="<s>"   ,							_SCREAMING_SNAKE_CASE="<unk>"   ,							_SCREAMING_SNAKE_CASE="<pad>"   ,							_SCREAMING_SNAKE_CASE="<mask>"   ,							_SCREAMING_SNAKE_CASE=False   ,							**_SCREAMING_SNAKE_CASE   ,							):


      '''simple docstring'''

      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else bos_token
      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else eos_token
      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else sep_token
      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else cls_token
      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else unk_token
      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      __lowerCamelCase								=				AddedToken(_SCREAMING_SNAKE_CASE   ,							lstrip=_SCREAMING_SNAKE_CASE   ,							rstrip=_SCREAMING_SNAKE_CASE  ) if isinstance(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  ) else mask_token

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

      with open(_SCREAMING_SNAKE_CASE   ,							encoding='utf-8'  ) as vocab_handle:
         __lowerCamelCase								=				json.load(_SCREAMING_SNAKE_CASE  )
      __lowerCamelCase								=				{v: k for k, v in self.encoder.items()}
      __lowerCamelCase								=				errors  # how to handle errors in decoding
      __lowerCamelCase								=				bytes_to_unicode()
      __lowerCamelCase								=				{v: k for k, v in self.byte_encoder.items()}
      with open(_SCREAMING_SNAKE_CASE   ,							encoding='utf-8'  ) as merges_handle:
         __lowerCamelCase								=				merges_handle.read().split('\n'  )[1:-1]
      __lowerCamelCase								=				[tuple(merge.split()  ) for merge in bpe_merges]
      __lowerCamelCase								=				dict(zip(_SCREAMING_SNAKE_CASE   ,							range(len(_SCREAMING_SNAKE_CASE  )  )  )  )
      __lowerCamelCase								=				{}
      __lowerCamelCase								=				add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      __lowerCamelCase								=				re.compile(r'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'  )







   @property
   def       _A							(  self  ):


      '''simple docstring'''

      return len(self.encoder  )







   def       _A							(  self  ):


      '''simple docstring'''

      return dict(self.encoder   ,							**self.added_tokens_encoder  )







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      if token in self.cache:
         return self.cache[token]
      __lowerCamelCase								=				tuple(_SCREAMING_SNAKE_CASE  )
      __lowerCamelCase								=				get_pairs(_SCREAMING_SNAKE_CASE  )

      if not pairs:
         return token

      while True:
         __lowerCamelCase								=				min(_SCREAMING_SNAKE_CASE   ,							key=lambda _SCREAMING_SNAKE_CASE  : self.bpe_ranks.get(_SCREAMING_SNAKE_CASE   ,							float('inf'  )  )  )
         if bigram not in self.bpe_ranks:
            break
         __lowerCamelCase		,__lowerCamelCase								=				bigram
         __lowerCamelCase								=				[]
         __lowerCamelCase								=				0
         while i < len(_SCREAMING_SNAKE_CASE  ):
            try:
               __lowerCamelCase								=				word.index(_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE  )
            except ValueError:
               new_word.extend(word[i:]  )
               break
            else:
               new_word.extend(word[i:j]  )
               __lowerCamelCase								=				j

            if word[i] == first and i < len(_SCREAMING_SNAKE_CASE  ) - 1 and word[i + 1] == second:
               new_word.append(first + second  )
               i += 2
            else:
               new_word.append(word[i]  )
               i += 1
         __lowerCamelCase								=				tuple(_SCREAMING_SNAKE_CASE  )
         __lowerCamelCase								=				new_word
         if len(_SCREAMING_SNAKE_CASE  ) == 1:
            break
         else:
            __lowerCamelCase								=				get_pairs(_SCREAMING_SNAKE_CASE  )
      __lowerCamelCase								=				' '.join(_SCREAMING_SNAKE_CASE  )
      __lowerCamelCase								=				word
      return word







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      __lowerCamelCase								=				[]
      for token in re.findall(self.pat   ,							_SCREAMING_SNAKE_CASE  ):
         __lowerCamelCase								=				''.join(
             self.byte_encoder[b] for b in token.encode('utf-8'  )  )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
         bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_SCREAMING_SNAKE_CASE  ).split(' '  )  )
      return bpe_tokens







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      return self.encoder.get(_SCREAMING_SNAKE_CASE   ,							self.encoder.get(self.unk_token  )  )







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      return self.decoder.get(_SCREAMING_SNAKE_CASE  )







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      __lowerCamelCase								=				''.join(_SCREAMING_SNAKE_CASE  )
      __lowerCamelCase								=				bytearray([self.byte_decoder[c] for c in text]  ).decode('utf-8'   ,							errors=self.errors  )
      return text







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE = None  ):


      '''simple docstring'''

      if not os.path.isdir(_SCREAMING_SNAKE_CASE  ):
         logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
         return
      __lowerCamelCase								=				os.path.join(
          _SCREAMING_SNAKE_CASE   ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']  )
      __lowerCamelCase								=				os.path.join(
          _SCREAMING_SNAKE_CASE   ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']  )

      with open(_SCREAMING_SNAKE_CASE   ,							'w'   ,							encoding='utf-8'  ) as f:
         f.write(json.dumps(self.encoder   ,							indent=2   ,							sort_keys=_SCREAMING_SNAKE_CASE   ,							ensure_ascii=_SCREAMING_SNAKE_CASE  ) + '\n'  )

      __lowerCamelCase								=				0
      with open(_SCREAMING_SNAKE_CASE   ,							'w'   ,							encoding='utf-8'  ) as writer:
         writer.write('#version: 0.2\n'  )
         for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,							key=lambda _SCREAMING_SNAKE_CASE  : kv[1]  ):
            if index != token_index:
               logger.warning(
                   F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                   ' Please check that the tokenizer is not corrupted!'  )
               __lowerCamelCase								=				token_index
            writer.write(' '.join(_SCREAMING_SNAKE_CASE  ) + '\n'  )
            index += 1

      return vocab_file, merge_file







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE = None  ):


      '''simple docstring'''

      if token_ids_a is None:
         return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      __lowerCamelCase								=				[self.cls_token_id]
      __lowerCamelCase								=				[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE = None   ,							_SCREAMING_SNAKE_CASE = False  ):


      '''simple docstring'''

      if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=_SCREAMING_SNAKE_CASE   ,							token_ids_a=_SCREAMING_SNAKE_CASE   ,							already_has_special_tokens=_SCREAMING_SNAKE_CASE  )

      if token_ids_a is None:
         return [1] + ([0] * len(_SCREAMING_SNAKE_CASE  )) + [1]
      return [1] + ([0] * len(_SCREAMING_SNAKE_CASE  )) + [1, 1] + ([0] * len(_SCREAMING_SNAKE_CASE  )) + [1]







   def       _A							(  self   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE = None  ):


      '''simple docstring'''

      __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       _A							(  self   ,							_SCREAMING_SNAKE_CASE   ,							_SCREAMING_SNAKE_CASE=False   ,							**_SCREAMING_SNAKE_CASE  ):


      '''simple docstring'''

      __lowerCamelCase								=				kwargs.pop('add_prefix_space'   ,							self.add_prefix_space  )
      if (is_split_into_words or add_prefix_space) and (len(_SCREAMING_SNAKE_CASE  ) > 0 and not text[0].isspace()):
         __lowerCamelCase								=				' ' + text
      return (text, kwargs)







"""simple docstring"""







from __future__ import annotations

from collections.abc import Callable



def 			A__						(  lowercase_    :  Callable[[int | float], int | float]			,   lowercase_    :  int | float			,   lowercase_    :  int | float			,   lowercase_    :  int = 100			,   )     ->       float:
   __lowerCamelCase								=				x_start
   __lowerCamelCase								=				fnc(lowercase_	)
   __lowerCamelCase								=				0.0

   for _ in range(lowercase_	):
      # Approximates small segments of curve as linear and solve
      # for trapezoidal area
      __lowerCamelCase								=				(x_end - x_start) / steps + xa
      __lowerCamelCase								=				fnc(lowercase_	)
      area += abs(fxa + fxa	) * (xa - xa) / 2

      # Increment step
      __lowerCamelCase								=				xa
      __lowerCamelCase								=				fxa
   return area


if __name__ == "__main__":



     def 			A__						(  lowercase_    :  Union[str, Any]	)     ->       int:
        return x**3

     print('''f(x) = x^3''')
     print('''The area between the curve, x = -10, x = 10 and the x axis is:''')
     _SCREAMING_SNAKE_CASE  :		Any        =      1_0
     while i <= 1_0_0_0_0_0:
          _SCREAMING_SNAKE_CASE  :		List[str]        =      trapezoidal_area(f, -5, 5, i)
          print(F"with {i} steps: {area}")
          i *= 1_0






