





'''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_roberta import RobertaTokenizer


lowercase__		:     Dict			=							logging.get_logger(__name__)

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

lowercase__		:     List[str]			=							{
    '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'
        ),
    },
    'tokenizer_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/tokenizer.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/tokenizer.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json',
        'roberta-base-openai-detector': (
            'https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'
        ),
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'
        ),
    },
}

lowercase__		:     Tuple			=							{
    'roberta-base': 5_12,
    'roberta-large': 5_12,
    'roberta-large-mnli': 5_12,
    'distilroberta-base': 5_12,
    'roberta-base-openai-detector': 5_12,
    'roberta-large-openai-detector': 5_12,
}
class 							__lowerCAmelCase	(       __magic_name__					):






       """simple docstring"""
       _snake_case      :	Optional[int]									=       VOCAB_FILES_NAMES
       _snake_case      :	Any									=       PRETRAINED_VOCAB_FILES_MAP
       _snake_case      :	Tuple									=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       _snake_case      :	Dict									=       ['input_ids', 'attention_mask']
       _snake_case      :	Any									=       RobertaTokenizer





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

            '''simple docstring'''




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

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

            _UpperCamelCase							       =			add_prefix_space

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

                 _UpperCamelCase							       =			False

                 if state.get('''add_prefix_space'''			,					lowerCAmelCase__	) != add_prefix_space:
                      _UpperCamelCase							       =			add_prefix_space
                      _UpperCamelCase							       =			True

                 if state.get('''trim_offsets'''			,					lowerCAmelCase__	) != trim_offsets:
                      _UpperCamelCase							       =			trim_offsets
                      _UpperCamelCase							       =			True

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





       @property
       def snake_case__		(				self  :						Optional[int]	)       ->	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 snake_case__		(				self  :						str			,					lowerCAmelCase__  :						Dict	)       ->	Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			AddedToken(lowerCAmelCase__			,					lstrip=lowerCAmelCase__			,					rstrip=lowerCAmelCase__	) if isinstance(lowerCAmelCase__			,					lowerCAmelCase__	) else value
            _UpperCamelCase							       =			value





       def snake_case__		(				self  :						Dict			,					*lowerCAmelCase__  :						Optional[Any]			,					**lowerCAmelCase__  :						Dict	)       ->	BatchEncoding:

            '''simple docstring'''




            _UpperCamelCase							       =			kwargs.get('''is_split_into_words'''			,					lowerCAmelCase__	)
            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(*lowerCAmelCase__			,					**lowerCAmelCase__	)





       def snake_case__		(				self  :						int			,					*lowerCAmelCase__  :						Any			,					**lowerCAmelCase__  :						List[str]	)       ->	BatchEncoding:

            '''simple docstring'''




            _UpperCamelCase							       =			kwargs.get('''is_split_into_words'''			,					lowerCAmelCase__	)

            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(*lowerCAmelCase__			,					**lowerCAmelCase__	)





       def snake_case__		(				self  :						Union[str, Any]			,					lowerCAmelCase__  :						str			,					lowerCAmelCase__  :						Optional[str] = None	)       ->	Tuple[str]:

            '''simple docstring'''




            _UpperCamelCase							       =			self._tokenizer.model.save(lowerCAmelCase__			,					name=lowerCAmelCase__	)
            return tuple(lowerCAmelCase__	)





       def snake_case__		(				self  :						Optional[Any]			,					lowerCAmelCase__  :						Optional[int]			,					lowerCAmelCase__  :						Any=None	)       ->	Optional[int]:

            '''simple docstring'''




            _UpperCamelCase							       =			[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 snake_case__		(				self  :						Dict			,					lowerCAmelCase__  :						List[int]			,					lowerCAmelCase__  :						Optional[List[int]] = None	)       ->	List[int]:

            '''simple docstring'''




            _UpperCamelCase							       =			[self.sep_token_id]
            _UpperCamelCase							       =			[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'''




from __future__ import annotations





def 	__lowerCamelCase			(      __lowerCAmelCase       :							Any      ,    __lowerCAmelCase       :							str      ,    __lowerCAmelCase       :							Any      ,    __lowerCAmelCase       :							int		)		->  Tuple:  # noqa: E741
   while r - l > 1:
      snake_case 						=   (l + r) // 2
      if v[m] >= key:
         snake_case 						=   m
      else:
         snake_case 						=   m  # noqa: E741
   return r





def 	__lowerCamelCase			(      __lowerCAmelCase       :							list[int]		)		->  int:
   if len(__lowerCAmelCase		) == 0:
      return 0

   snake_case 						=   [0] * len(__lowerCAmelCase		)
   snake_case 						=   1

   snake_case 						=   v[0]

   for i in range(1      ,    len(__lowerCAmelCase		)		):
      if v[i] < tail[0]:
         snake_case 						=   v[i]
      elif v[i] > tail[length - 1]:
         snake_case 						=   v[i]
         length += 1
      else:
         snake_case 						=   v[i]

   return length


if __name__ == "__main__":
 import doctest

 doctest.testmod()

