

# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation

import warnings

from .state import AcceleratorState, GradientState


warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")






class 						__magic_name__    :


 def __init__(						self		: Optional[Any]			,						lowerCAmelCase__		: str			,						lowerCAmelCase__		: List[str]			,						lowerCAmelCase__		: bool = True			,						lowerCAmelCase__		: bool = False    )    ->      Tuple:
   UpperCAmelCase					      =  scheduler
   UpperCAmelCase					      =  optimizers if isinstance(lowerCAmelCase__			,						(list, tuple)    ) else [optimizers]
   UpperCAmelCase					      =  split_batches
   UpperCAmelCase					      =  step_with_optimizer
   UpperCAmelCase					      =  GradientState()


 def _UpperCamelCase	(						self		: int			,						*lowerCAmelCase__		: Dict			,						**lowerCAmelCase__		: Optional[Any]    )    ->      Optional[Any]:
   if not self.step_with_optimizer:
     # No link between scheduler and optimizer -> just step
     self.scheduler.step(*lowerCAmelCase__			,						**lowerCAmelCase__    )
     return

   # Otherwise, first make sure the optimizer was stepped.
   if not self.gradient_state.sync_gradients:
     if self.gradient_state.adjust_scheduler:
       self.scheduler._step_count += 1
     return

   for opt in self.optimizers:
     if opt.step_was_skipped:
       return
   if self.split_batches:
     # Split batches -> the training dataloader batch size is not changed so one step per training step
     self.scheduler.step(*lowerCAmelCase__			,						**lowerCAmelCase__    )
   else:
     # Otherwise the training dataloader batch size was multiplied by `num_processes`, so we need to do
     # num_processes steps per training step
     UpperCAmelCase					      =  AcceleratorState().num_processes
     for _ in range(lowerCAmelCase__    ):
       # Special case when using OneCycle and `drop_last` was not used
       if hasattr(self.scheduler			,						"total_steps"    ):
         if self.scheduler._step_count <= self.scheduler.total_steps:
           self.scheduler.step(*lowerCAmelCase__			,						**lowerCAmelCase__    )
       else:
         self.scheduler.step(*lowerCAmelCase__			,						**lowerCAmelCase__    )


 def _UpperCamelCase	(						self		: Dict    )    ->      List[Any]:
   return self.scheduler.get_last_lr()


 def _UpperCamelCase	(						self		: Optional[int]    )    ->      str:
   return self.scheduler.state_dict()


 def _UpperCamelCase	(						self		: Tuple			,						lowerCAmelCase__		: str    )    ->      Union[str, Any]:
   self.scheduler.load_state_dict(lowerCAmelCase__    )


 def _UpperCamelCase	(						self		: Dict    )    ->      str:
   return self.scheduler.get_lr()


 def _UpperCamelCase	(						self		: Union[str, Any]			,						*lowerCAmelCase__		: Union[str, Any]			,						**lowerCAmelCase__		: List[str]    )    ->      List[Any]:
   return self.scheduler.print_lr(*lowerCAmelCase__			,						**lowerCAmelCase__    )






from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowerCAmelCase__       = {"UserAgent": UserAgent().random}
def      _lowerCAmelCase(	__A			):
  UpperCAmelCase					      =  script.contents[0]
  UpperCAmelCase					      =  json.loads(data[data.find("{\"config\""			) : -1]			)
  return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]






class 						__magic_name__    :


 def __init__(						self		: Optional[Any]			,						lowerCAmelCase__		: Optional[int]    )    ->      Any:
   UpperCAmelCase					      =  f"https://www.instagram.com/{username}/"
   UpperCAmelCase					      =  self.get_json()


 def _UpperCamelCase	(						self		: List[str]    )    ->      dict:
   UpperCAmelCase					      =  requests.get(self.url			,						headers=lowerCAmelCase__    ).text
   UpperCAmelCase					      =  BeautifulSoup(lowerCAmelCase__			,						"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		: Tuple    )    ->      str:
   return f"{self.__class__.__name__}('{self.username}')"


 def __str__(						self		: Optional[int]    )    ->      str:
   return f"{self.fullname} ({self.username}) is {self.biography}"


 @property
 def _UpperCamelCase	(						self		: Any    )    ->      str:
   return self.user_data["username"]


 @property
 def _UpperCamelCase	(						self		: List[Any]    )    ->      str:
   return self.user_data["full_name"]


 @property
 def _UpperCamelCase	(						self		: List[str]    )    ->      str:
   return self.user_data["biography"]


 @property
 def _UpperCamelCase	(						self		: Optional[int]    )    ->      str:
   return self.user_data["business_email"]


 @property
 def _UpperCamelCase	(						self		: str    )    ->      str:
   return self.user_data["external_url"]


 @property
 def _UpperCamelCase	(						self		: int    )    ->      int:
   return self.user_data["edge_followed_by"]["count"]


 @property
 def _UpperCamelCase	(						self		: List[Any]    )    ->      int:
   return self.user_data["edge_follow"]["count"]


 @property
 def _UpperCamelCase	(						self		: List[str]    )    ->      int:
   return self.user_data["edge_owner_to_timeline_media"]["count"]


 @property
 def _UpperCamelCase	(						self		: Tuple    )    ->      str:
   return self.user_data["profile_pic_url_hd"]


 @property
 def _UpperCamelCase	(						self		: Optional[int]    )    ->      bool:
   return self.user_data["is_verified"]


 @property
 def _UpperCamelCase	(						self		: Optional[Any]    )    ->      bool:
   return self.user_data["is_private"]

def      _lowerCAmelCase(	__A = "github"			):
  import os

  if os.environ.get("CI"			):
    return  # test failing on GitHub Actions
  UpperCAmelCase					      =  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 > 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 = }")



