




"""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


A_      			=       logging.get_logger(__name__)

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

A_      			=       {
    '''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'''
        ),
    },
}

A_      			=       {
    '''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       lowercase(  __a				):







 '''simple docstring'''





 lowercase__				      =      VOCAB_FILES_NAMES
 lowercase__				      =      PRETRAINED_VOCAB_FILES_MAP
 lowercase__				      =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__				      =      ["input_ids", "attention_mask"]
 lowercase__				      =      RobertaTokenizer


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




   '''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_,   )

   _snake_case							:	Tuple			=						json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
   if pre_tok_state.get("""add_prefix_space""",   a_	) != add_prefix_space:
     _snake_case							:	List[str]			=						getattr(a_,   pre_tok_state.pop("""type"""	)	)
     _snake_case							:	int			=						add_prefix_space
     _snake_case							:	Optional[int]			=						pre_tok_class(**a_	)

   _snake_case							:	Dict			=						add_prefix_space

   _snake_case							:	Optional[Any]			=						"""post_processor"""
   _snake_case							:	Any			=						getattr(self.backend_tokenizer,   a_,   a_	)
   if tokenizer_component_instance:
     _snake_case							:	List[str]			=						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:
       _snake_case							:	Any			=						tuple(state["""sep"""]	)
     if "cls" in state:
       _snake_case							:	List[str]			=						tuple(state["""cls"""]	)

     _snake_case							:	List[Any]			=						False

     if state.get("""add_prefix_space""",   a_	) != add_prefix_space:
       _snake_case							:	Dict			=						add_prefix_space
       _snake_case							:	Any			=						True

     if state.get("""trim_offsets""",   a_	) != trim_offsets:
       _snake_case							:	int			=						trim_offsets
       _snake_case							:	Tuple			=						True

     if changes_to_apply:
       _snake_case							:	Optional[Any]			=						getattr(a_,   state.pop("""type"""	)	)
       _snake_case							:	Tuple			=						component_class(**a_	)
       setattr(self.backend_tokenizer,   a_,   a_	)


 @property
 def 				UpperCamelCase_     (       self:	Tuple	):




   '''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 				UpperCamelCase_     (       self:	List[Any],   a_:	Union[str, Any]	):




   '''simple docstring'''



   _snake_case							:	Union[str, Any]			=						AddedToken(a_,   lstrip=a_,   rstrip=a_	) if isinstance(a_,   a_	) else value
   _snake_case							:	Tuple			=						value


 def 				UpperCamelCase_     (       self:	Optional[int],   *a_:	Any,   **a_:	List[Any]	):




   '''simple docstring'''



   _snake_case							:	Optional[Any]			=						kwargs.get("""is_split_into_words""",   a_	)
   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(*a_,   **a_	)


 def 				UpperCamelCase_     (       self:	Any,   *a_:	Dict,   **a_:	Any	):




   '''simple docstring'''



   _snake_case							:	Tuple			=						kwargs.get("""is_split_into_words""",   a_	)

   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(*a_,   **a_	)


 def 				UpperCamelCase_     (       self:	Dict,   a_:	str,   a_:	Optional[str] = None	):




   '''simple docstring'''



   _snake_case							:	str			=						self._tokenizer.model.save(a_,   name=a_	)
   return tuple(a_	)


 def 				UpperCamelCase_     (       self:	str,   a_:	str,   a_:	str=None	):




   '''simple docstring'''



   _snake_case							:	List[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 				UpperCamelCase_     (       self:	Tuple,   a_:	List[int],   a_:	Optional[List[int]] = None	):




   '''simple docstring'''



   _snake_case							:	List[str]			=						[self.sep_token_id]
   _snake_case							:	Optional[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]








"""simple docstring"""


from __future__ import annotations

import math


def       UpperCAmelCase__ (snake_case__							:      int					):
  """simple docstring"""

  if 1 < number < 4:
    # 2 and 3 are primes
    return True
  elif number < 2 or number % 2 == 0 or number % 3 == 0:
    # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
    return False

  # All primes number are in format of 6k +/- 1
  for i in range(5	,     int(math.sqrt(snake_case__					) + 1					)	,     6					):
    if number % i == 0 or number % (i + 2) == 0:
      return False
  return True


A_      			=       [num for num in range(3, 10_00_01, 2) if not is_prime(num)]


def       UpperCAmelCase__ (snake_case__							:      int					):
  """simple docstring"""

  if not isinstance(snake_case__	,     snake_case__					):
    raise ValueError("""n must be an integer"""					)
  if n <= 0:
    raise ValueError("""n must be >= 0"""					)

  _snake_case							:	Any			=						[]
  for num in range(len(snake_case__					)					):
    _snake_case							:	Optional[int]			=						0
    while 2 * i * i <= odd_composites[num]:
      _snake_case							:	Optional[int]			=						odd_composites[num] - 2 * i * i
      if is_prime(snake_case__					):
        break
      i += 1
    else:
      list_nums.append(odd_composites[num]					)
      if len(snake_case__					) == n:
        return list_nums

  return []


def       UpperCAmelCase__ ():
  """simple docstring"""

  return compute_nums(1					)[0]


if __name__ == "__main__":
     print(F'''{solution() = }''')


