



from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_tf_available():
    import tensorflow as tf


UpperCAmelCase_									=							logging.get_logger(__name__)





@dataclass
class 		UpperCAmelCase						(						snake_case_				):
   SCREAMING_SNAKE_CASE__							=     [
       '''no_inference''',
       '''no_cuda''',
       '''no_tpu''',
       '''no_speed''',
       '''no_memory''',
       '''no_env_print''',
       '''no_multi_process''',
   ]





   def __init__(	self       ,     **_lowerCAmelCase			):
         for deprecated_arg in self.deprecated_args:
               if deprecated_arg in kwargs:
                     _lowerCAmelCase 			=  deprecated_arg[3:]
                     _lowerCAmelCase 			=  not kwargs.pop(_lowerCAmelCase			)
                     logger.warning(
                         F'''{deprecated_arg} is depreciated. Please use --no-{positive_arg} or'''
                         F''' {positive_arg}={kwargs[positive_arg]}'''			)
         _lowerCAmelCase 			=  kwargs.pop('''tpu_name'''       ,     self.tpu_name			)
         _lowerCAmelCase 			=  kwargs.pop('''device_idx'''       ,     self.device_idx			)
         _lowerCAmelCase 			=  kwargs.pop('''eager_mode'''       ,     self.eager_mode			)
         _lowerCAmelCase 			=  kwargs.pop('''use_xla'''       ,     self.use_xla			)
         super().__init__(**_lowerCAmelCase			)

   SCREAMING_SNAKE_CASE__							=     field(
       default=snake_case_       ,metadata={'''help''': '''Name of TPU'''}       ,)
   SCREAMING_SNAKE_CASE__							=     field(
       default=0       ,metadata={'''help''': '''CPU / GPU device index. Defaults to 0.'''}       ,)
   SCREAMING_SNAKE_CASE__							=     field(default=snake_case_       ,metadata={'''help''': '''Benchmark models in eager model.'''}				)
   SCREAMING_SNAKE_CASE__							=     field(
       default=snake_case_       ,metadata={
           '''help''': '''Benchmark models using XLA JIT compilation. Note that `eager_model` has to be set to `False`.'''
       }       ,)





   @cached_property
   def 	__lowerCAmelCase							(	self			):
         requires_backends(self       ,     ['''tf''']			)
         _lowerCAmelCase 			=  None
         if self.tpu:
               try:
                     if self.tpu_name:
                           _lowerCAmelCase 			=  tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name			)
                     else:
                           _lowerCAmelCase 			=  tf.distribute.cluster_resolver.TPUClusterResolver()
               except ValueError:
                     _lowerCAmelCase 			=  None
         return tpu





   @cached_property
   def 	__lowerCAmelCase							(	self			):
         requires_backends(self       ,     ['''tf''']			)
         if self.is_tpu:
               tf.config.experimental_connect_to_cluster(self._setup_tpu			)
               tf.tpu.experimental.initialize_tpu_system(self._setup_tpu			)

               _lowerCAmelCase 			=  tf.distribute.TPUStrategy(self._setup_tpu			)
         else:
               # currently no multi gpu is allowed
               if self.is_gpu:
                     # TODO: Currently only single GPU is supported
                     tf.config.set_visible_devices(self.gpu_list[self.device_idx]       ,     '''GPU'''			)
                     _lowerCAmelCase 			=  tf.distribute.OneDeviceStrategy(device=F'''/gpu:{self.device_idx}'''			)
               else:
                     tf.config.set_visible_devices([]       ,     '''GPU'''			)  # disable GPU
                     _lowerCAmelCase 			=  tf.distribute.OneDeviceStrategy(device=F'''/cpu:{self.device_idx}'''			)

         return strategy





   @property
   def 	__lowerCAmelCase							(	self			):
         requires_backends(self       ,     ['''tf''']			)
         return self._setup_tpu is not None





   @property
   def 	__lowerCAmelCase							(	self			):
         requires_backends(self       ,     ['''tf''']			)
         return self._setup_strategy





   @property
   def 	__lowerCAmelCase							(	self			):
         requires_backends(self       ,     ['''tf''']			)
         return tf.config.list_physical_devices('''GPU'''			)





   @property
   def 	__lowerCAmelCase							(	self			):
         requires_backends(self       ,     ['''tf''']			)
         if self.cuda:
               return len(self.gpu_list			)
         return 0





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.n_gpu > 0




from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

UpperCAmelCase_									=							{"UserAgent": UserAgent().random}
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Dict				)->dict:
      _lowerCAmelCase 			=  script.contents[0]
      _lowerCAmelCase 			=  json.loads(data[data.find('''{"config"'''				) : -1]				)
      return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]





class 		UpperCAmelCase						:





   def __init__(	self       ,     _lowerCAmelCase			):
         _lowerCAmelCase 			=  F'''https://www.instagram.com/{username}/'''
         _lowerCAmelCase 			=  self.get_json()





   def 	__lowerCAmelCase							(	self			):
         _lowerCAmelCase 			=  requests.get(self.url       ,     headers=_lowerCAmelCase			).text
         _lowerCAmelCase 			=  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			):
         return F'''{self.__class__.__name__}(\'{self.username}\')'''





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





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





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.user_data["full_name"]





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





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





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.user_data["external_url"]





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.user_data["edge_followed_by"]["count"]





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





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.user_data["edge_owner_to_timeline_media"]["count"]





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.user_data["profile_pic_url_hd"]





   @property
   def 	__lowerCAmelCase							(	self			):
         return self.user_data["is_verified"]





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






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

      if os.environ.get('''CI'''				):
            return  # test failing on GitHub Actions
      _lowerCAmelCase 			=  InstagramUser(_SCREAMING_SNAKE_CASE				)
      assert instagram_user.user_data
      assert isinstance(instagram_user.user_data     ,				_SCREAMING_SNAKE_CASE				)
      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()
    UpperCAmelCase_									=							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 = }""")