





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


_snake_case           =			logging.get_logger(__name__)

_snake_case           =			{"""vocab_file""": """sentencepiece.bpe.model"""}

_snake_case           =			{
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

_snake_case           =			{
    """camembert-base""": 512,
}

_snake_case           =			"""▁"""





class  lowerCAmelCase							(       lowercase_ ):
  __lowerCamelCase		=      VOCAB_FILES_NAMES
  __lowerCamelCase		=      PRETRAINED_VOCAB_FILES_MAP
  __lowerCamelCase		=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowerCamelCase		=      ['input_ids', 'attention_mask']







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






     '''simple docstring'''





     lowercase__			       =  AddedToken(_lowercase   ,							lstrip=_lowercase   ,							rstrip=_lowercase ) if isinstance(_lowercase   ,							_lowercase ) else mask_token

     lowercase__			       =  {} 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   ,							additional_special_tokens=_lowercase   ,							sp_model_kwargs=self.sp_model_kwargs   ,							**_lowercase   ,							)
     lowercase__			       =  spm.SentencePieceProcessor(**self.sp_model_kwargs )
     self.sp_model.Load(str(_lowercase ) )
     lowercase__			       =  vocab_file
     # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
     # sentencepiece vocabulary (this is the case for <s> and </s>
     lowercase__			       =  {"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
     lowercase__			       =  len(self.fairseq_tokens_to_ids )
     lowercase__			       =  len(self.sp_model ) + len(self.fairseq_tokens_to_ids )
     lowercase__			       =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}







  def   UpperCAmelCase					(      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]
     lowercase__			       =  [self.cls_token_id]
     lowercase__			       =  [self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep







  def   UpperCAmelCase					(      self  :List[str]   ,							_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   UpperCAmelCase					(      self  :List[str]   ,							_lowercase  :List[int]   ,							_lowercase  :Optional[List[int]] = None ):






     '''simple docstring'''





     lowercase__			       =  [self.sep_token_id]
     lowercase__			       =  [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   UpperCAmelCase					(      self  :str ):






     '''simple docstring'''





     return len(self.fairseq_tokens_to_ids ) + len(self.sp_model )







  def   UpperCAmelCase					(      self  :Dict ):






     '''simple docstring'''





     lowercase__			       =  {self.convert_ids_to_tokens(_lowercase ): i for i in range(self.vocab_size )}
     vocab.update(self.added_tokens_encoder )
     return vocab







  def   UpperCAmelCase					(      self  :Any   ,							_lowercase  :str ):






     '''simple docstring'''





     return self.sp_model.encode(_lowercase   ,							out_type=_lowercase )







  def   UpperCAmelCase					(      self  :List[Any]   ,							_lowercase  :Tuple ):






     '''simple docstring'''





     if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
     elif self.sp_model.PieceToId(_lowercase ) == 0:
        # Convert sentence piece unk token to fairseq unk token index
        return self.unk_token_id
     return self.fairseq_offset + self.sp_model.PieceToId(_lowercase )







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							_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   UpperCAmelCase					(      self  :Dict   ,							_lowercase  :int ):






     '''simple docstring'''





     lowercase__			       =  []
     lowercase__			       =  ""
     lowercase__			       =  False
     for token in tokens:
        # make sure that special tokens are not decoded using sentencepiece model
        if token in self.all_special_tokens:
           if not prev_is_special:
              out_string += " "
           out_string += self.sp_model.decode(_lowercase ) + token
           lowercase__			       =  True
           lowercase__			       =  []
        else:
           current_sub_tokens.append(_lowercase )
           lowercase__			       =  False
     out_string += self.sp_model.decode(_lowercase )
     return out_string.strip()







  def __getstate__(      self  :Any ):






     '''simple docstring'''





     lowercase__			       =  self.__dict__.copy()
     lowercase__			       =  None
     return state







  def __setstate__(      self  :List[Any]   ,							_lowercase  :Any ):






     '''simple docstring'''





     lowercase__			       =  d

     # for backward compatibility
     if not hasattr(self   ,							"sp_model_kwargs" ):
        lowercase__			       =  {}

     lowercase__			       =  spm.SentencePieceProcessor(**self.sp_model_kwargs )
     self.sp_model.Load(self.vocab_file )







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							_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
     lowercase__			       =  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:
           lowercase__			       =  self.sp_model.serialized_model_proto()
           fi.write(_lowercase )

     return (out_vocab_file,)













from collections import namedtuple

import requests
from lxml import html  # type: ignore

_snake_case           =			namedtuple("""covid_data""", """cases deaths recovered""")


def _A       (   __magic_name__ = "https://www.worldometers.info/coronavirus/"	):
   lowercase__			       =  "//div[@class = \"maincounter-number\"]/span/text()"
   return covid_data(*html.fromstring(requests.get(__magic_name__	).content	).xpath(__magic_name__	)	)


_snake_case           =			"""Total COVID-19 cases in the world: {}
Total deaths due to COVID-19 in the world: {}
Total COVID-19 patients recovered in the world: {}"""







print(fmt.format(*covid_stats()))






