


'''simple docstring'''




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


_a   :   Tuple												=   logging.get_logger(__name__)

_a   :   Dict												=   {"vocab_file": "spm_char.model"}

_a   :   Optional[int]												=   {
    "vocab_file": {
        "microsoft/speecht5_asr": "https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model",
        "microsoft/speecht5_tts": "https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model",
        "microsoft/speecht5_vc": "https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model",
    }
}

_a   :   List[Any]												=   {
    "microsoft/speecht5_asr": 1_024,
    "microsoft/speecht5_tts": 1_024,
    "microsoft/speecht5_vc": 1_024,
}




class 			_lowercase (	__lowercase							):
   _SCREAMING_SNAKE_CASE  :  Any          =	VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE  :  Optional[Any]          =	PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE  :  Optional[int]          =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _SCREAMING_SNAKE_CASE  :  Optional[int]          =	["input_ids", "attention_mask"]
   def __init__(						self       :      Union[str, Any]       ,   SCREAMING_SNAKE_CASE_       :      Tuple       ,   SCREAMING_SNAKE_CASE_       :      str="<s>"       ,   SCREAMING_SNAKE_CASE_       :      Dict="</s>"       ,   SCREAMING_SNAKE_CASE_       :      Optional[Any]="<unk>"       ,   SCREAMING_SNAKE_CASE_       :      List[str]="<pad>"       ,   SCREAMING_SNAKE_CASE_       :      Optional[Dict[str, Any]] = None       ,   **SCREAMING_SNAKE_CASE_       :      Dict       ,   ) ->							None:
        __snake_case           =						{} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=SCREAMING_SNAKE_CASE_       ,   eos_token=SCREAMING_SNAKE_CASE_       ,   unk_token=SCREAMING_SNAKE_CASE_       ,   pad_token=SCREAMING_SNAKE_CASE_       ,   sp_model_kwargs=self.sp_model_kwargs       ,   **SCREAMING_SNAKE_CASE_       ,   )

        __snake_case           =						vocab_file

        __snake_case           =						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
        self.sp_model.Load(SCREAMING_SNAKE_CASE_      )
   @property
   def a  (						self       :      int      ) ->							Dict:
        return self.sp_model.get_piece_size()
   def a  (						self       :      List[str]      ) ->							Dict:
        __snake_case           =						{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_      ): i for i in range(self.vocab_size      )}
        vocab.update(self.added_tokens_encoder      )
        return vocab
   def __getstate__(						self       :      Any      ) ->							str:
        __snake_case           =						self.__dict__.copy()
        __snake_case           =						None
        return state
   def __setstate__(						self       :      Optional[Any]       ,   SCREAMING_SNAKE_CASE_       :      Union[str, Any]      ) ->							Any:
        __snake_case           =						d

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

        __snake_case           =						spm.SentencePieceProcessor(**self.sp_model_kwargs      )
        self.sp_model.Load(self.vocab_file      )
   def a  (						self       :      Any       ,   SCREAMING_SNAKE_CASE_       :      str      ) ->							List[str]:
        return self.sp_model.encode(SCREAMING_SNAKE_CASE_       ,   out_type=SCREAMING_SNAKE_CASE_      )
   def a  (						self       :      Any       ,   SCREAMING_SNAKE_CASE_       :      int      ) ->							str:
        return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE_      )
   def a  (						self       :      Optional[int]       ,   SCREAMING_SNAKE_CASE_       :      List[str]      ) ->							Any:
        __snake_case           =						self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE_      )
        return token
   def a  (						self       :      Optional[Any]       ,   SCREAMING_SNAKE_CASE_       :      Dict      ) ->							Optional[int]:
        __snake_case           =						[]
        __snake_case           =						''
        for token in tokens:
             # make sure that special tokens are not decoded using sentencepiece model
             if token in self.all_special_tokens:
                  out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE_      ) + token
                  __snake_case           =						[]
             else:
                  current_sub_tokens.append(SCREAMING_SNAKE_CASE_      )
        out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE_      )
        return out_string.strip()
   def a  (						self       :      Union[str, Any]       ,   SCREAMING_SNAKE_CASE_       :      List[Any]       ,   SCREAMING_SNAKE_CASE_       :      List[str]=None      ) ->							List[int]:
        if token_ids_a is None:
             return token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return token_ids_a + token_ids_a + [self.eos_token_id]
   def a  (						self       :      Tuple       ,   SCREAMING_SNAKE_CASE_       :      List[int]       ,   SCREAMING_SNAKE_CASE_       :      Optional[List[int]] = None       ,   SCREAMING_SNAKE_CASE_       :      bool = False      ) ->							List[int]:
        if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=SCREAMING_SNAKE_CASE_       ,   token_ids_a=SCREAMING_SNAKE_CASE_       ,   already_has_special_tokens=SCREAMING_SNAKE_CASE_      )

        __snake_case           =						[1]
        if token_ids_a is None:
             return ([0] * len(SCREAMING_SNAKE_CASE_      )) + suffix_ones
        return ([0] * len(SCREAMING_SNAKE_CASE_      )) + ([0] * len(SCREAMING_SNAKE_CASE_      )) + suffix_ones





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

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

        return (out_vocab_file,)






from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowercase   =	{'''UserAgent''': UserAgent().random}



def   __lowerCAmelCase    (				UpperCAmelCase__					:   Optional[int]							)	->     dict:
							lowerCamelCase_					=       script.contents[0]
							lowerCamelCase_					=       json.loads(data[data.find("""{\"config\""""							) : -1]							)
							return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]





class    __A:

					def __init__(						self       :  int ,       __UpperCamelCase       :  List[str] ):
												lowerCamelCase_					=       F'''https://www.instagram.com/{username}/'''
												lowerCamelCase_					=       self.get_json()

					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       requests.get(self.url ,       headers=__UpperCamelCase ).text
												lowerCamelCase_					=       BeautifulSoup(__UpperCamelCase ,       """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       :  Dict ):
												return F'''{self.__class__.__name__}(\'{self.username}\')'''

					def __str__(						self       :  Optional[Any] ):
												return F'''{self.fullname} ({self.username}) is {self.biography}'''

					@property
					def  lowercase__   (						self       :  Dict ):
												return self.user_data["username"]

					@property
					def  lowercase__   (						self       :  List[Any] ):
												return self.user_data["full_name"]

					@property
					def  lowercase__   (						self       :  Any ):
												return self.user_data["biography"]

					@property
					def  lowercase__   (						self       :  int ):
												return self.user_data["business_email"]

					@property
					def  lowercase__   (						self       :  List[str] ):
												return self.user_data["external_url"]

					@property
					def  lowercase__   (						self       :  List[Any] ):
												return self.user_data["edge_followed_by"]["count"]

					@property
					def  lowercase__   (						self       :  str ):
												return self.user_data["edge_follow"]["count"]

					@property
					def  lowercase__   (						self       :  List[str] ):
												return self.user_data["edge_owner_to_timeline_media"]["count"]

					@property
					def  lowercase__   (						self       :  List[str] ):
												return self.user_data["profile_pic_url_hd"]

					@property
					def  lowercase__   (						self       :  Optional[Any] ):
												return self.user_data["is_verified"]



					@property
					def  lowercase__   (						self       :  int ):
												return self.user_data["is_private"]



def   __lowerCAmelCase    (				UpperCAmelCase__					:   str = "github"							)	->     None:
							import os

							if os.environ.get("""CI"""							):
														return  # test failing on GitHub Actions
							lowerCamelCase_					=       InstagramUser(UpperCAmelCase__							)
							assert instagram_user.user_data
							assert isinstance(instagram_user.user_data      ,					UpperCAmelCase__							)
							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 > 1_5_0
							assert instagram_user.number_of_followers > 1_2_0_0_0_0
							assert instagram_user.number_of_followings > 1_5
							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()
		lowercase   =	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 = }""")





