






"""simple docstring"""





from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase_	:				Any										= logging.get_logger(__name__)

UpperCamelCase_	:				List[Any]										= {
    """facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}


class      _lowercase (     lowerCAmelCase						):
      _a   :     Any								=   '''nllb-moe'''
      _a   :     Tuple								=   ['''past_key_values''']
      _a   :     Any								=   {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}


      def __init__(    self				:	int							,   a				:	List[str]=1_2_8_1_1_2							,   a				:	Optional[Any]=1_0_2_4							,   a				:	List[Any]=1_2							,   a				:	Dict=4_0_9_6							,   a				:	Dict=1_6							,   a				:	Tuple=1_2							,   a				:	str=4_0_9_6							,   a				:	Dict=1_6							,   a				:	List[Any]=0.0_5							,   a				:	Dict=0.0_5							,   a				:	Union[str, Any]=True							,   a				:	Optional[int]=True							,   a				:	Optional[int]="relu"							,   a				:	Union[str, Any]=1_0_2_4							,   a				:	Union[str, Any]=0.1							,   a				:	List[Any]=0.1							,   a				:	List[Any]=0.0							,   a				:	Dict=0.0_2							,   a				:	Optional[int]=2							,   a				:	Tuple=True							,   a				:	Optional[int]=False							,   a				:	Union[str, Any]="float32"							,   a				:	Optional[int]=False							,   a				:	str=1_2_8							,   a				:	str=6_4							,   a				:	Tuple=4							,   a				:	Optional[Any]=4							,   a				:	str=0.0_0_1							,   a				:	Any=0.0_0_1							,   a				:	str="all"							,   a				:	Optional[int]=False							,   a				:	Dict=False							,   a				:	str=1.0							,   a				:	List[str]=0.2							,   a				:	Union[str, Any]=1							,   a				:	Union[str, Any]=0							,   a				:	Tuple=2							,   a				:	Optional[Any]=False							,   **a				:	str							,   ):





            """simple docstring"""







            __snake_case      :    Any  			=vocab_size
            __snake_case      :    List[Any]  			=max_position_embeddings
            __snake_case      :    Union[str, Any]  			=d_model
            __snake_case      :    List[str]  			=encoder_ffn_dim
            __snake_case      :    Tuple  			=encoder_layers
            __snake_case      :    Tuple  			=encoder_attention_heads
            __snake_case      :    Tuple  			=decoder_ffn_dim
            __snake_case      :    Dict  			=decoder_layers
            __snake_case      :    List[str]  			=decoder_attention_heads
            __snake_case      :    Union[str, Any]  			=dropout
            __snake_case      :    List[str]  			=attention_dropout
            __snake_case      :    str  			=activation_dropout
            __snake_case      :    List[str]  			=activation_function
            __snake_case      :    Dict  			=init_std
            __snake_case      :    Union[str, Any]  			=encoder_layerdrop
            __snake_case      :    int  			=decoder_layerdrop
            __snake_case      :    Tuple  			=use_cache
            __snake_case      :    Optional[Any]  			=encoder_layers
            __snake_case      :    Optional[Any]  			=scale_embedding  # scale factor will be sqrt(d_model) if True
            __snake_case      :    Union[str, Any]  			=router_z_loss_coef
            __snake_case      :    Union[str, Any]  			=router_aux_loss_coef
            __snake_case      :    Any  			=decoder_sparse_step
            __snake_case      :    Optional[int]  			=encoder_sparse_step
            __snake_case      :    Optional[int]  			=num_experts
            __snake_case      :    Optional[int]  			=expert_capacity
            __snake_case      :    int  			=router_bias
            if router_dtype not in ["float32", "float16", "bfloat16"]:
                  raise ValueError(f'''`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'''						)
            __snake_case      :    Any  			=router_dtype

            __snake_case      :    Union[str, Any]  			=router_ignore_padding_tokens
            __snake_case      :    Dict  			=batch_prioritized_routing
            __snake_case      :    Tuple  			=second_expert_policy
            __snake_case      :    List[Any]  			=normalize_router_prob_before_dropping
            __snake_case      :    str  			=moe_eval_capacity_token_fraction
            __snake_case      :    Optional[int]  			=moe_token_dropout
            __snake_case      :    Optional[int]  			=output_router_logits
            super().__init__(
                pad_token_id=a							,   bos_token_id=a							,   eos_token_id=a							,   is_encoder_decoder=a							,   decoder_start_token_id=a							,   **a							,   )










"""simple docstring"""





from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

UpperCamelCase_	:				Tuple										= {"""UserAgent""": UserAgent().random}



def     __lowercase					(    a :				str )					->					dict:
      __snake_case      :    Union[str, Any]  			=script.contents[0]
      __snake_case      :    List[str]  			=json.loads(data[data.find('''{"config"''' ) : -1] )
      return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]


class      _lowercase :


      def __init__(    self				:	int							,   a				:	Dict						):





            """simple docstring"""







            __snake_case      :    Dict  			=f'''https://www.instagram.com/{username}/'''
            __snake_case      :    str  			=self.get_json()


      def _UpperCamelCase						(    self				:	Union[str, Any]						):





            """simple docstring"""







            __snake_case      :    List[str]  			=requests.get(self.url							,   headers=a						).text
            __snake_case      :    int  			=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				:	int						):





            """simple docstring"""







            return f'''{self.__class__.__name__}(\'{self.username}\')'''


      def __str__(    self				:	Any						):





            """simple docstring"""







            return f'''{self.fullname} ({self.username}) is {self.biography}'''


      @property
      def _UpperCamelCase						(    self				:	Union[str, Any]						):





            """simple docstring"""







            return self.user_data["username"]


      @property
      def _UpperCamelCase						(    self				:	Dict						):





            """simple docstring"""







            return self.user_data["full_name"]


      @property
      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            return self.user_data["biography"]


      @property
      def _UpperCamelCase						(    self				:	Dict						):





            """simple docstring"""







            return self.user_data["business_email"]


      @property
      def _UpperCamelCase						(    self				:	Optional[int]						):





            """simple docstring"""







            return self.user_data["external_url"]


      @property
      def _UpperCamelCase						(    self				:	Dict						):





            """simple docstring"""







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


      @property
      def _UpperCamelCase						(    self				:	int						):





            """simple docstring"""







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


      @property
      def _UpperCamelCase						(    self				:	Tuple						):





            """simple docstring"""







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


      @property
      def _UpperCamelCase						(    self				:	Dict						):





            """simple docstring"""







            return self.user_data["profile_pic_url_hd"]


      @property
      def _UpperCamelCase						(    self				:	str						):





            """simple docstring"""







            return self.user_data["is_verified"]







      @property
      def _UpperCamelCase						(    self				:	Dict						):





            """simple docstring"""







            return self.user_data["is_private"]



def     __lowercase					(    a :				str = "github" )					->					None:
      import os

      if os.environ.get('''CI''' ):
            return  # test failing on GitHub Actions
      __snake_case      :    Union[str, Any]  			=InstagramUser(a )
      assert instagram_user.user_data
      assert isinstance(instagram_user.user_data       ,		a )
      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 > 120_000
      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()
    UpperCamelCase_	:				Optional[int]										= 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 = }''')


