






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


lowerCAmelCase_           = logging.get_logger(__name__)

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

lowerCAmelCase_           = {
    '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'
        ),
    },
}

lowerCAmelCase_           = {
    'roberta-base': 512,
    'roberta-large': 512,
    'roberta-large-mnli': 512,
    'distilroberta-base': 512,
    'roberta-base-openai-detector': 512,
    'roberta-large-openai-detector': 512,
}
class      UpperCamelCase (				snake_case__ ):







		"""simple docstring"""



		snake_case    =   VOCAB_FILES_NAMES
		snake_case    =   PRETRAINED_VOCAB_FILES_MAP
		snake_case    =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		snake_case    =   ["input_ids", "attention_mask"]
		snake_case    =   RobertaTokenizer
		def __init__(  self		:       Any						,_SCREAMING_SNAKE_CASE		:       Dict=None						,_SCREAMING_SNAKE_CASE		:       Dict=None						,_SCREAMING_SNAKE_CASE		:       int=None						,_SCREAMING_SNAKE_CASE		:       Tuple="replace"						,_SCREAMING_SNAKE_CASE		:       Optional[Any]="<s>"						,_SCREAMING_SNAKE_CASE		:       List[str]="</s>"						,_SCREAMING_SNAKE_CASE		:       Dict="</s>"						,_SCREAMING_SNAKE_CASE		:       Optional[Any]="<s>"						,_SCREAMING_SNAKE_CASE		:       List[Any]="<unk>"						,_SCREAMING_SNAKE_CASE		:       Optional[Any]="<pad>"						,_SCREAMING_SNAKE_CASE		:       Optional[int]="<mask>"						,_SCREAMING_SNAKE_CASE		:       Tuple=False						,_SCREAMING_SNAKE_CASE		:       Tuple=True						,**_SCREAMING_SNAKE_CASE		:       Any						,)    ->   List[Any]:


						'''simple docstring'''
						super().__init__(
						    _SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE						,tokenizer_file=_SCREAMING_SNAKE_CASE						,errors=_SCREAMING_SNAKE_CASE						,bos_token=_SCREAMING_SNAKE_CASE						,eos_token=_SCREAMING_SNAKE_CASE						,sep_token=_SCREAMING_SNAKE_CASE						,cls_token=_SCREAMING_SNAKE_CASE						,unk_token=_SCREAMING_SNAKE_CASE						,pad_token=_SCREAMING_SNAKE_CASE						,mask_token=_SCREAMING_SNAKE_CASE						,add_prefix_space=_SCREAMING_SNAKE_CASE						,trim_offsets=_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE						,)

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

						A	 =      add_prefix_space

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

										A	 =      False

										if state.get('add_prefix_space'						,_SCREAMING_SNAKE_CASE		) != add_prefix_space:
														A	 =      add_prefix_space
														A	 =      True

										if state.get('trim_offsets'						,_SCREAMING_SNAKE_CASE		) != trim_offsets:
														A	 =      trim_offsets
														A	 =      True

										if changes_to_apply:
														A	 =      getattr(_SCREAMING_SNAKE_CASE						,state.pop('type'		)		)
														A	 =      component_class(**_SCREAMING_SNAKE_CASE		)
														setattr(self.backend_tokenizer						,_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
		@property
		def       A(  self		:       List[Any]		)    ->   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       A(  self		:       List[Any]						,_SCREAMING_SNAKE_CASE		:       Any		)    ->   Optional[int]:


						'''simple docstring'''
						A	 =      AddedToken(_SCREAMING_SNAKE_CASE						,lstrip=_SCREAMING_SNAKE_CASE						,rstrip=_SCREAMING_SNAKE_CASE		) if isinstance(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		) else value
						A	 =      value
		def       A(  self		:       Any						,*_SCREAMING_SNAKE_CASE		:       List[str]						,**_SCREAMING_SNAKE_CASE		:       Optional[int]		)    ->   BatchEncoding:


						'''simple docstring'''
						A	 =      kwargs.get('is_split_into_words'						,_SCREAMING_SNAKE_CASE		)
						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(*_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Tuple						,*_SCREAMING_SNAKE_CASE		:       Tuple						,**_SCREAMING_SNAKE_CASE		:       List[Any]		)    ->   BatchEncoding:


						'''simple docstring'''
						A	 =      kwargs.get('is_split_into_words'						,_SCREAMING_SNAKE_CASE		)

						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(*_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Tuple						,_SCREAMING_SNAKE_CASE		:       str						,_SCREAMING_SNAKE_CASE		:       Optional[str] = None		)    ->   Tuple[str]:


						'''simple docstring'''
						A	 =      self._tokenizer.model.save(_SCREAMING_SNAKE_CASE						,name=_SCREAMING_SNAKE_CASE		)
						return tuple(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       Tuple						,_SCREAMING_SNAKE_CASE		:       Dict=None		)    ->   List[str]:


						'''simple docstring'''
						A	 =      [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       A(  self		:       str						,_SCREAMING_SNAKE_CASE		:       List[int]						,_SCREAMING_SNAKE_CASE		:       Optional[List[int]] = None		)    ->   List[int]:


						'''simple docstring'''
						A	 =      [self.sep_token_id]
						A	 =      [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 collections.abc import Callable
class      UpperCamelCase :







		"""simple docstring"""



		def __init__(  self		:       Tuple						,_SCREAMING_SNAKE_CASE		:       Callable | None = None		)    ->   None:


						'''simple docstring'''
						# Stores actual heap items.
						A	 =      []
						# Stores indexes of each item for supporting updates and deletion.
						A	 =      {}
						# Stores current size of heap.
						A	 =      0
						# Stores function used to evaluate the score of an item on which basis ordering
						# will be done.
						A	 =      key or (lambda _SCREAMING_SNAKE_CASE		: x)
		def       A(  self		:       Tuple						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int | None:


						'''simple docstring'''
						return int((i - 1) / 2		) if i > 0 else None
		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int | None:


						'''simple docstring'''
						A	 =      int(2 * i + 1		)
						return left if 0 < left < self.size else None
		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int | None:


						'''simple docstring'''
						A	 =      int(2 * i + 2		)
						return right if 0 < right < self.size else None
		def       A(  self		:       List[str]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A ,		A	 =      (
						    self.pos_map[self.arr[j][0]],
						    self.pos_map[self.arr[i][0]],
						)
						# Then swap the items in the list.
						A ,		A	 =      self.arr[j], self.arr[i]
		def       A(  self		:       List[str]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   bool:


						'''simple docstring'''
						return self.arr[i][1] < self.arr[j][1]
		def       A(  self		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   int:


						'''simple docstring'''
						A	 =      self._left(_SCREAMING_SNAKE_CASE		)
						A	 =      self._right(_SCREAMING_SNAKE_CASE		)
						A	 =      i

						if left is not None and not self._cmp(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
										A	 =      left
						if right is not None and not self._cmp(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
										A	 =      right

						return valid_parent
		def       A(  self		:       Any						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A	 =      self._parent(_SCREAMING_SNAKE_CASE		)
						while parent is not None and not self._cmp(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		):
										self._swap(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
										A ,		A	 =      parent, self._parent(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       List[Any]						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A	 =      self._get_valid_parent(_SCREAMING_SNAKE_CASE		)
						while valid_parent != index:
										self._swap(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
										A ,		A	 =      valid_parent, self._get_valid_parent(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Optional[Any]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						if item not in self.pos_map:
										return
						A	 =      self.pos_map[item]
						A	 =      [item, self.key(_SCREAMING_SNAKE_CASE		)]
						# Make sure heap is right in both up and down direction.
						# Ideally only one of them will make any change.
						self._heapify_up(_SCREAMING_SNAKE_CASE		)
						self._heapify_down(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						if item not in self.pos_map:
										return
						A	 =      self.pos_map[item]
						del self.pos_map[item]
						A	 =      self.arr[self.size - 1]
						A	 =      index
						self.size -= 1
						# Make sure heap is right in both up and down direction. Ideally only one
						# of them will make any change- so no performance loss in calling both.
						if self.size > index:
										self._heapify_up(_SCREAMING_SNAKE_CASE		)
										self._heapify_down(_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Optional[Any]						,_SCREAMING_SNAKE_CASE		:       int						,_SCREAMING_SNAKE_CASE		:       int		)    ->   None:


						'''simple docstring'''
						A	 =      len(self.arr		)
						if arr_len == self.size:
										self.arr.append([item, self.key(_SCREAMING_SNAKE_CASE		)]		)
						else:
										A	 =      [item, self.key(_SCREAMING_SNAKE_CASE		)]
						A	 =      self.size
						self.size += 1
						self._heapify_up(self.size - 1		)
		def       A(  self		:       str		)    ->   tuple | None:


						'''simple docstring'''
						return self.arr[0] if self.size else None







		def       A(  self		:       Any		)    ->   tuple | None:


						'''simple docstring'''
						A	 =      self.get_top()
						if top_item_tuple:
										self.delete_item(top_item_tuple[0]		)
						return top_item_tuple







def      snake_case		(							):
				pass


if __name__ == "__main__":
					import doctest

					doctest.testmod()





