

"""simple docstring"""






import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


_lowerCAmelCase						=		logging.get_logger(__name__)


_lowerCAmelCase						=		{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all LED models at https://huggingface.co/models?filter=LED
_lowerCAmelCase						=		{
    """vocab_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json""",
    },
}

_lowerCAmelCase						=		{
    """allenai/led-base-16384""": 1_6_3_8_4,
}

@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 		lowerCamelCase__		(					):

    '''simple docstring'''



    _lowerCAmelCase       :   Any  =    (
        list(range(ord('!'   ) ,   ord('~'   ) + 1   )   ) + list(range(ord('¡'   ) ,   ord('¬'   ) + 1   )   ) + list(range(ord('®'   ) ,   ord('ÿ'   ) + 1   )   )
    )
    _lowerCAmelCase       :   Union[str, Any]  =    bs[:]
    _lowerCAmelCase       :   Union[str, Any]  =    0
    for b in range(2**8   ):
        if b not in bs:
            bs.append(_lowerCamelCase   )
            cs.append(2**8 + n   )
            n += 1
    _lowerCAmelCase       :   str  =    [chr(_lowerCamelCase   ) for n in cs]
    return dict(zip(_lowerCamelCase ,   _lowerCamelCase   )   )

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    _lowerCAmelCase       :   int  =    set()
    _lowerCAmelCase       :   Optional[Any]  =    word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)   )
        _lowerCAmelCase       :   Optional[Any]  =    char
    return pairs







class 	__UpperCamelCase    (    a__						):
  _UpperCAmelCase          =		VOCAB_FILES_NAMES
  _UpperCAmelCase          =		PRETRAINED_VOCAB_FILES_MAP
  _UpperCAmelCase          =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _UpperCAmelCase          =		["input_ids", "attention_mask"]

  def __init__(		self    ,_A    ,_A    ,_A="replace"    ,_A="<s>"    ,_A="</s>"    ,_A="</s>"    ,_A="<s>"    ,_A="<unk>"    ,_A="<pad>"    ,_A="<mask>"    ,_A=False    ,**_A    ,):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[int]  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else bos_token
      _lowerCAmelCase       :   Dict  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else eos_token
      _lowerCAmelCase       :   Union[str, Any]  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else sep_token
      _lowerCAmelCase       :   Any  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else cls_token
      _lowerCAmelCase       :   Tuple  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else unk_token
      _lowerCAmelCase       :   Optional[int]  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      _lowerCAmelCase       :   str  =    AddedToken(_A    ,lstrip=_A    ,rstrip=_A      ) if isinstance(_A    ,_A      ) else mask_token

      super().__init__(
          errors=_A    ,bos_token=_A    ,eos_token=_A    ,unk_token=_A    ,sep_token=_A    ,cls_token=_A    ,pad_token=_A    ,mask_token=_A    ,add_prefix_space=_A    ,**_A    ,)

      with open(_A    ,encoding='utf-8'      ) as vocab_handle:
          _lowerCAmelCase       :   Tuple  =    json.load(_A      )
      _lowerCAmelCase       :   Optional[int]  =    {v: k for k, v in self.encoder.items()}
      _lowerCAmelCase       :   Optional[Any]  =    errors  # how to handle errors in decoding
      _lowerCAmelCase       :   Optional[int]  =    bytes_to_unicode()
      _lowerCAmelCase       :   int  =    {v: k for k, v in self.byte_encoder.items()}
      with open(_A    ,encoding='utf-8'      ) as merges_handle:
          _lowerCAmelCase       :   Tuple  =    merges_handle.read().split('\n'      )[1:-1]
      _lowerCAmelCase       :   Optional[Any]  =    [tuple(merge.split()      ) for merge in bpe_merges]
      _lowerCAmelCase       :   Optional[int]  =    dict(zip(_A    ,range(len(_A      )      )      )      )
      _lowerCAmelCase       :   Any  =    {}
      _lowerCAmelCase       :   List[Any]  =    add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      _lowerCAmelCase       :   int  =    re.compile(r'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'      )

  @property
  # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return len(self.encoder      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return dict(self.encoder    ,**self.added_tokens_encoder      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      if token in self.cache:
          return self.cache[token]
      _lowerCAmelCase       :   int  =    tuple(_A      )
      _lowerCAmelCase       :   str  =    get_pairs(_A      )

      if not pairs:
          return token

      while True:
          _lowerCAmelCase       :   Dict  =    min(_A    ,key=lambda _A      : self.bpe_ranks.get(_A    ,float('inf'      )      )      )
          if bigram not in self.bpe_ranks:
              break
          _lowerCAmelCase,					_lowerCAmelCase       :   List[str]  =    bigram
          _lowerCAmelCase       :   Tuple  =    []
          _lowerCAmelCase       :   Tuple  =    0
          while i < len(_A      ):
              try:
                  _lowerCAmelCase       :   int  =    word.index(_A    ,_A      )
              except ValueError:
                  new_word.extend(word[i:]      )
                  break
              else:
                  new_word.extend(word[i:j]      )
                  _lowerCAmelCase       :   int  =    j

              if word[i] == first and i < len(_A      ) - 1 and word[i + 1] == second:
                  new_word.append(first + second      )
                  i += 2
              else:
                  new_word.append(word[i]      )
                  i += 1
          _lowerCAmelCase       :   Optional[Any]  =    tuple(_A      )
          _lowerCAmelCase       :   Tuple  =    new_word
          if len(_A      ) == 1:
              break
          else:
              _lowerCAmelCase       :   List[str]  =    get_pairs(_A      )
      _lowerCAmelCase       :   Tuple  =    ' '.join(_A      )
      _lowerCAmelCase       :   List[Any]  =    word
      return word

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[int]  =    []
      for token in re.findall(self.pat    ,_A      ):
          _lowerCAmelCase       :   int  =    ''.join(
              self.byte_encoder[b] for b in token.encode('utf-8'      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
          bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_A      ).split(' '      )      )
      return bpe_tokens

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      return self.encoder.get(_A    ,self.encoder.get(self.unk_token      )      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      return self.decoder.get(_A      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   int  =    ''.join(_A      )
      _lowerCAmelCase       :   Optional[Any]  =    bytearray([self.byte_decoder[c] for c in text]      ).decode('utf-8'    ,errors=self.errors      )
      return text

  def __lowerCamelCase		(		self    ,_A    ,_A = None      ):
      '''simple docstring'''

      if not os.path.isdir(_A      ):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
          return
      _lowerCAmelCase       :   Any  =    os.path.join(
          _A    ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )
      _lowerCAmelCase       :   List[str]  =    os.path.join(
          _A    ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']      )

      with open(_A    ,'w'    ,encoding='utf-8'      ) as f:
          f.write(json.dumps(self.encoder    ,indent=2    ,sort_keys=_A    ,ensure_ascii=_A      ) + '\n'      )

      _lowerCAmelCase       :   Optional[int]  =    0
      with open(_A    ,'w'    ,encoding='utf-8'      ) as writer:
          writer.write('#version: 0.2\n'      )
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,key=lambda _A      : kv[1]      ):
              if index != token_index:
                  logger.warning(
                      F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                      ' Please check that the tokenizer is not corrupted!'      )
                  _lowerCAmelCase       :   Union[str, Any]  =    token_index
              writer.write(' '.join(_A      ) + '\n'      )
              index += 1

      return vocab_file, merge_file

  def __lowerCamelCase		(		self    ,_A    ,_A = None      ):
      '''simple docstring'''

      if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      _lowerCAmelCase       :   List[Any]  =    [self.cls_token_id]
      _lowerCAmelCase       :   List[Any]  =    [self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep

  def __lowerCamelCase		(		self    ,_A    ,_A = None    ,_A = False      ):
      '''simple docstring'''

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

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

  def __lowerCamelCase		(		self    ,_A    ,_A = None      ):
      '''simple docstring'''

      _lowerCAmelCase       :   int  =    [self.sep_token_id]
      _lowerCAmelCase       :   str  =    [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]

  def __lowerCamelCase		(		self    ,_A    ,_A=False    ,**_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[str]  =    kwargs.pop('add_prefix_space'    ,self.add_prefix_space      )
      if (is_split_into_words or add_prefix_space) and (len(_A      ) > 0 and not text[0].isspace()):
          _lowerCAmelCase       :   Union[str, Any]  =    ' ' + text
      return (text, kwargs)







  def __lowerCamelCase		(		self    ,_A    ,_A = None    ,_A = PaddingStrategy.DO_NOT_PAD    ,_A = None    ,_A = None    ,):
      '''simple docstring'''

      _lowerCAmelCase       :   Any  =    super()._pad(
          encoded_inputs=_A    ,max_length=_A    ,padding_strategy=_A    ,pad_to_multiple_of=_A    ,return_attention_mask=_A    ,)

      # Load from model defaults
      if return_attention_mask is None:
          _lowerCAmelCase       :   Union[str, Any]  =    'attention_mask' in self.model_input_names

      if return_attention_mask and "global_attention_mask" in encoded_inputs:
          _lowerCAmelCase       :   Optional[Any]  =    encoded_inputs[self.model_input_names[0]]
          # `global_attention_mask` need to have the same length as other (sequential) inputs.
          _lowerCAmelCase       :   Any  =    len(encoded_inputs['global_attention_mask']      ) != len(_A      )

          if needs_to_be_padded:
              _lowerCAmelCase       :   Optional[Any]  =    len(_A      ) - len(encoded_inputs['global_attention_mask']      )

              if self.padding_side == "right":
                  # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                  _lowerCAmelCase       :   Optional[Any]  =    (
                      encoded_inputs['global_attention_mask'] + [-1] * difference
                  )
              elif self.padding_side == "left":
                  _lowerCAmelCase       :   List[Any]  =    [-1] * difference + encoded_inputs[
                      'global_attention_mask'
                  ]
              else:
                  raise ValueError('Invalid padding strategy:' + str(self.padding_side      )      )

      return encoded_inputs








"""simple docstring"""






from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

_lowerCAmelCase						=		{"""UserAgent""": UserAgent().random}

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    _lowerCAmelCase       :   Any  =    script.contents[0]
    _lowerCAmelCase       :   Union[str, Any]  =    json.loads(data[data.find('{"config"'   ) : -1]   )
    return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]







class 	__UpperCamelCase    :

  def __init__(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[Any]  =    F"""https://www.instagram.com/{username}/"""
      _lowerCAmelCase       :   str  =    self.get_json()

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   str  =    requests.get(self.url    ,headers=_A      ).text
      _lowerCAmelCase       :   Optional[Any]  =    BeautifulSoup(_A    ,'html.parser'      ).find_all('script'      )
      try:
          return extract_user_profile(scripts[4]      )
      except (json.decoder.JSONDecodeError, KeyError):
          return extract_user_profile(scripts[3]      )

  def __repr__(		self      ):
      '''simple docstring'''

      return F"""{self.__class__.__name__}('{self.username}')"""

  def __str__(		self      ):
      '''simple docstring'''

      return F"""{self.fullname} ({self.username}) is {self.biography}"""

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["username"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["full_name"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["biography"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["business_email"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["external_url"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["edge_followed_by"]["count"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["edge_follow"]["count"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["edge_owner_to_timeline_media"]["count"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["profile_pic_url_hd"]

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["is_verified"]







  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return self.user_data["is_private"]





def 		lowerCamelCase__		(					_lowerCamelCase = "github"   ):

    '''simple docstring'''



    import os

    if os.environ.get('CI'   ):
        return  # test failing on GitHub Actions
    _lowerCAmelCase       :   Tuple  =    InstagramUser(_lowerCamelCase   )
    assert instagram_user.user_data
    assert isinstance(instagram_user.user_data ,   _lowerCamelCase   )
    assert instagram_user.username == username
    if username != "github":
        return
    assert instagram_user.fullname == "GitHub"
    assert instagram_user.biography == "Built for developers."
    assert instagram_user.number_of_posts > 150
    assert instagram_user.number_of_followers > 120000
    assert instagram_user.number_of_followings > 15
    assert instagram_user.email == "support@github.com"
    assert instagram_user.website == "https://github.com/readme"
    assert instagram_user.profile_picture_url.startswith('https://instagram.'   )
    assert instagram_user.is_verified is True
    assert instagram_user.is_private is False


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 _lowerCAmelCase						=		InstagramUser("""github""")
 print(instagram_user)
 print(F'''{instagram_user.number_of_posts = }''')
 print(F'''{instagram_user.number_of_followers = }''')
 print(F'''{instagram_user.number_of_followings = }''')
 print(F'''{instagram_user.email = }''')
 print(F'''{instagram_user.website = }''')
 print(F'''{instagram_user.profile_picture_url = }''')
 print(F'''{instagram_user.is_verified = }''')
 print(F'''{instagram_user.is_private = }''')





