






"""simple docstring"""






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


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

UpperCAmelCase_     :				Optional[int]         =				"""▁"""

UpperCAmelCase_     :				Tuple         =				{"""vocab_file""": """sentencepiece.bpe.model"""}

UpperCAmelCase_     :				Tuple         =				{
    """vocab_file""": {
        """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large-finetuned-conll02-dutch""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll02-spanish""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-english""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-german""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

UpperCAmelCase_     :				Optional[int]         =				{
    """xlm-roberta-base""": 512,
    """xlm-roberta-large""": 512,
    """xlm-roberta-large-finetuned-conll02-dutch""": 512,
    """xlm-roberta-large-finetuned-conll02-spanish""": 512,
    """xlm-roberta-large-finetuned-conll03-english""": 512,
    """xlm-roberta-large-finetuned-conll03-german""": 512,
}




class 							lowerCAmelCase__       (    UpperCAmelCase__				):






      '''simple docstring'''

      __UpperCamelCase							=						VOCAB_FILES_NAMES
      __UpperCamelCase							=						PRETRAINED_VOCAB_FILES_MAP
      __UpperCamelCase							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __UpperCamelCase							=						["input_ids", "attention_mask"]
      def __init__(		self  :						Optional[Any]		,			lowercase_  :						Tuple		,			lowercase_  :						int="<s>"		,			lowercase_  :						List[Any]="</s>"		,			lowercase_  :						List[Any]="</s>"		,			lowercase_  :						List[str]="<s>"		,			lowercase_  :						Dict="<unk>"		,			lowercase_  :						Dict="<pad>"		,			lowercase_  :						Tuple="<mask>"		,			lowercase_  :						Optional[Dict[str, Any]] = None		,			**lowercase_  :						List[str]		,			):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Any							=	AddedToken(lowercase_		,			lstrip=lowercase_		,			rstrip=lowercase_) if isinstance(lowercase_		,			lowercase_) else mask_token

          SCREAMING_SNAKE_CASE_   :						List[str]							=	{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              bos_token=lowercase_		,			eos_token=lowercase_		,			unk_token=lowercase_		,			sep_token=lowercase_		,			cls_token=lowercase_		,			pad_token=lowercase_		,			mask_token=lowercase_		,			sp_model_kwargs=self.sp_model_kwargs		,			**lowercase_		,			)

          SCREAMING_SNAKE_CASE_   :						Any							=	spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.Load(str(lowercase_))
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	vocab_file

          # Original fairseq vocab and spm vocab must be "aligned":
          # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
          # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
          # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
          # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

          # Mimic fairseq token-to-id alignment for the first 4 token
          SCREAMING_SNAKE_CASE_   :						str							=	{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

          # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
          SCREAMING_SNAKE_CASE_   :						int							=	1

          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	len(self.sp_model) + self.fairseq_offset
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	{v: k for k, v in self.fairseq_tokens_to_ids.items()}
      def __getstate__(		self  :						str):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	self.__dict__.copy()
          SCREAMING_SNAKE_CASE_   :						Dict							=	None
          SCREAMING_SNAKE_CASE_   :						Tuple							=	self.sp_model.serialized_model_proto()
          return state
      def __setstate__(		self  :						int		,			lowercase_  :						Optional[int]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	d

          # for backward compatibility
          if not hasattr(self		,			'''sp_model_kwargs'''):
              SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	{}

          SCREAMING_SNAKE_CASE_   :						List[Any]							=	spm.SentencePieceProcessor(**self.sp_model_kwargs)
          self.sp_model.LoadFromSerializedProto(self.sp_model_proto)
      def _SCREAMING_SNAKE_CASE				(		self  :						int		,			lowercase_  :						List[int]		,			lowercase_  :						Optional[List[int]] = None):




          '''simple docstring'''


          if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	[self.cls_token_id]
          SCREAMING_SNAKE_CASE_   :						Dict							=	[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep
      def _SCREAMING_SNAKE_CASE				(		self  :						Optional[int]		,			lowercase_  :						List[int]		,			lowercase_  :						Optional[List[int]] = None		,			lowercase_  :						bool = False):




          '''simple docstring'''


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

          if token_ids_a is None:
              return [1] + ([0] * len(lowercase_)) + [1]
          return [1] + ([0] * len(lowercase_)) + [1, 1] + ([0] * len(lowercase_)) + [1]
      def _SCREAMING_SNAKE_CASE				(		self  :						str		,			lowercase_  :						List[int]		,			lowercase_  :						Optional[List[int]] = None):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Any							=	[self.sep_token_id]
          SCREAMING_SNAKE_CASE_   :						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]
      @property
      def _SCREAMING_SNAKE_CASE				(		self  :						List[Any]):




          '''simple docstring'''


          return len(self.sp_model) + self.fairseq_offset + 1  # Add the <mask> token
      def _SCREAMING_SNAKE_CASE				(		self  :						Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	{self.convert_ids_to_tokens(lowercase_): i for i in range(self.vocab_size)}
          vocab.update(self.added_tokens_encoder)
          return vocab
      def _SCREAMING_SNAKE_CASE				(		self  :						Optional[Any]		,			lowercase_  :						str):




          '''simple docstring'''


          return self.sp_model.encode(lowercase_		,			out_type=lowercase_)
      def _SCREAMING_SNAKE_CASE				(		self  :						List[str]		,			lowercase_  :						int):




          '''simple docstring'''


          if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
          SCREAMING_SNAKE_CASE_   :						int							=	self.sp_model.PieceToId(lowercase_)

          # Need to return unknown token if the SP model returned 0
          return spm_id + self.fairseq_offset if spm_id else self.unk_token_id
      def _SCREAMING_SNAKE_CASE				(		self  :						List[str]		,			lowercase_  :						List[str]):




          '''simple docstring'''


          if index in self.fairseq_ids_to_tokens:
              return self.fairseq_ids_to_tokens[index]
          return self.sp_model.IdToPiece(index - self.fairseq_offset)
      def _SCREAMING_SNAKE_CASE				(		self  :						Optional[Any]		,			lowercase_  :						List[str]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_   :						Any							=	''''''.join(lowercase_).replace(lowercase_		,			''' ''').strip()
          return out_string



      def _SCREAMING_SNAKE_CASE				(		self  :						str		,			lowercase_  :						str		,			lowercase_  :						Optional[str] = None):




          '''simple docstring'''


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

          if os.path.abspath(self.vocab_file) != os.path.abspath(lowercase_) and os.path.isfile(self.vocab_file):
              copyfile(self.vocab_file		,			lowercase_)
          elif not os.path.isfile(self.vocab_file):
              with open(lowercase_		,			'''wb''') as fi:
                  SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	self.sp_model.serialized_model_proto()
                  fi.write(lowercase_)

          return (out_vocab_file,)










"""simple docstring"""






from math import isqrt



def       _A    (__a							)				-> list[int]:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	[True] * max_number
    for i in range(2					,       isqrt(max_number - 1							) + 1							):
        if is_prime[i]:
            for j in range(i**2					,       __a					,       __a							):
                SCREAMING_SNAKE_CASE_   :						Tuple							=	False

    return [i for i in range(2					,       __a							) if is_prime[i]]



def       _A    (__a = 10**8							)				-> int:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						Any							=	calculate_prime_numbers(max_number // 2							)

    SCREAMING_SNAKE_CASE_   :						List[str]							=	0
    SCREAMING_SNAKE_CASE_   :						Any							=	0
    SCREAMING_SNAKE_CASE_   :						List[str]							=	len(__a							) - 1
    while left <= right:
        while prime_numbers[left] * prime_numbers[right] >= max_number:
            right -= 1
        semiprimes_count += right - left + 1
        left += 1

    return semiprimes_count


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


