






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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


snake_case__   :						str													=   logging.get_logger(__name__)

snake_case__   :						Union[str, Any]													=   """▁"""

snake_case__   :						List[Any]													=   {"""vocab_file""": """sentencepiece.bpe.model"""}

snake_case__   :						Optional[Any]													=   {
    """vocab_file""": {
        """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model""",
    }
}

snake_case__   :						int													=   {
    """facebook/xglm-564M""": 2_0_4_8,
}


class     _a							(	__UpperCAmelCase     ):






  """simple docstring"""





  A_						       = VOCAB_FILES_NAMES
  A_						       = PRETRAINED_VOCAB_FILES_MAP
  A_						       = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A_						       = ['''input_ids''', '''attention_mask''']




  def __init__(  self		,		_UpperCAmelCase		,		_UpperCAmelCase="<s>"		,		_UpperCAmelCase="</s>"		,		_UpperCAmelCase="</s>"		,		_UpperCAmelCase="<s>"		,		_UpperCAmelCase="<unk>"		,		_UpperCAmelCase="<pad>"		,		_UpperCAmelCase = None		,		**_UpperCAmelCase		,		)      ->			None:
     UpperCamelCase_						=  {} if sp_model_kwargs is None else sp_model_kwargs

     # Compatibility with the original tokenizer
     UpperCamelCase_						=  7
     UpperCamelCase_						=  [f"""<madeupword{i}>""" for i in range(self.num_madeup_words			)]

     UpperCamelCase_						=  kwargs.get('additional_special_tokens'		,		[]			)
     kwargs["additional_special_tokens"] += [
         word for word in madeup_words if word not in kwargs["additional_special_tokens"]
     ]

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

     UpperCamelCase_						=  spm.SentencePieceProcessor(**self.sp_model_kwargs			)
     self.sp_model.Load(str(lowerCamelCase__			)			)
     UpperCamelCase_						=  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'

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

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

     UpperCamelCase_						=  len(self.sp_model			)
     UpperCamelCase_						=  {f"""<madeupword{i}>""": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words			)}
     self.fairseq_tokens_to_ids.update(lowerCamelCase__			)

     UpperCamelCase_						=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}




  def __getstate__(  self			)      ->			Dict:
     UpperCamelCase_						=  self.__dict__.copy()
     UpperCamelCase_						=  None
     UpperCamelCase_						=  self.sp_model.serialized_model_proto()
     return state




  def __setstate__(  self		,		_UpperCAmelCase			)      ->			Optional[int]:
     UpperCamelCase_						=  d

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

     UpperCamelCase_						=  spm.SentencePieceProcessor(**self.sp_model_kwargs			)
     self.sp_model.LoadFromSerializedProto(self.sp_model_proto			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase = None			)      ->			List[int]:

     if token_ids_a is None:
        return [self.sep_token_id] + token_ids_a
     UpperCamelCase_						=  [self.sep_token_id]
     return sep + token_ids_a + sep + sep + token_ids_a




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase = None		,		_UpperCAmelCase = False			)      ->			List[int]:

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

     if token_ids_a is None:
        return [1] + ([0] * len(lowerCamelCase__			))
     return [1] + ([0] * len(lowerCamelCase__			)) + [1, 1] + ([0] * len(lowerCamelCase__			))




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase = None			)      ->			List[int]:
     UpperCamelCase_						=  [self.sep_token_id]

     if token_ids_a is None:
        return len(sep + token_ids_a			) * [0]
     return len(sep + token_ids_a + sep + sep + token_ids_a			) * [0]




  @property
  def  _UpperCAmelCase  (  self			)      ->			Union[str, Any]:
     return len(self.sp_model			) + self.fairseq_offset + self.num_madeup_words




  def  _UpperCAmelCase  (  self			)      ->			int:
     UpperCamelCase_						=  {self.convert_ids_to_tokens(lowerCamelCase__			): i for i in range(self.vocab_size			)}
     vocab.update(self.added_tokens_encoder			)
     return vocab




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			List[str]:
     return self.sp_model.encode(lowerCamelCase__		,		out_type=lowerCamelCase__			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			int:
     if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
     UpperCamelCase_						=  self.sp_model.PieceToId(lowerCamelCase__			)

     # 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  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			int:
     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		,		_UpperCAmelCase			)      ->			int:
     UpperCamelCase_						=  """""".join(lowerCamelCase__			).replace(lowerCamelCase__		,		' '			).strip()
     return out_string




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase = None			)      ->			Tuple[str]:
     if not os.path.isdir(lowerCamelCase__			):
        logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""			)
        return
     UpperCamelCase_						=  os.path.join(
         lowerCamelCase__		,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)

     if os.path.abspath(self.vocab_file			) != os.path.abspath(lowerCamelCase__			) and os.path.isfile(self.vocab_file			):
        copyfile(self.vocab_file		,		lowerCamelCase__			)
     elif not os.path.isfile(self.vocab_file			):
        with open(lowerCamelCase__		,		'wb'			) as fi:
           UpperCamelCase_						=  self.sp_model.serialized_model_proto()
           fi.write(lowerCamelCase__			)

     return (out_vocab_file,)









"""simple docstring"""


import requests
from bsa import BeautifulSoup


def    _lowerCamelCase   (     lowerCamelCase__	:							str = "https://www.worldometers.info/coronavirus"  ):
 lowercase__       :       Optional[Any]				=						BeautifulSoup(requests.get(lowerCamelCase__  ).text       ,		"""html.parser"""  )
 lowercase__       :       Union[str, Any]				=						soup.findAll("""h1"""  )
 lowercase__       :       List[str]				=						soup.findAll("""div"""       ,		{"""class""": """maincounter-number"""}  )
 keys += soup.findAll("""span"""       ,		{"""class""": """panel-title"""}  )
 values += soup.findAll("""div"""       ,		{"""class""": """number-table-main"""}  )
 return {key.text.strip(): value.text.strip() for key, value in zip(lowerCamelCase__       ,		lowerCamelCase__  )}


if __name__ == "__main__":
   print('\033[1m' + 'COVID-19 Status of the World' + '\033[0m\n')
   for key, value in world_covidaa_stats().items():
      print(F"{key}\n{value}\n")