import os
import unittest
from tempfile import TemporaryDirectory

import torch
import torch.nn as nn

from accelerate.utils import (
    OffloadedWeightsLoader,
    extract_submodules_state_dict,
    load_offloaded_weight,
    offload_state_dict,
    offload_weight,
)

class        UpperCamelCase						(				nn.Module				):





						def __init__(self						)				->				Tuple:
												super().__init__()
												UpperCamelCase_		:							Optional[int]  =		nn.Linear(3			,     4						)
												UpperCamelCase_		:							Optional[int]  =		nn.BatchNormad(4						)
												UpperCamelCase_		:							Union[str, Any]  =		nn.Linear(4			,     5						)





						def        A_							(self			,     __UpperCamelCase						)				->				Dict:
												return self.lineara(self.batchnorm(self.lineara(__UpperCamelCase						)						)						)


class        UpperCamelCase						(				unittest.TestCase				):





						def        A_							(self						)				->				Optional[int]:
												UpperCamelCase_		:							int  =		ModelForTest()
												with TemporaryDirectory() as tmp_dir:
																		offload_state_dict(__UpperCamelCase			,     model.state_dict()						)
																		UpperCamelCase_		:							Tuple  =		os.path.join(__UpperCamelCase			,     """index.json"""						)
																		self.assertTrue(os.path.isfile(__UpperCamelCase						)						)
																		# TODO: add tests on what is inside the index

																		for key in ["linear1.weight", "linear1.bias", "linear2.weight", "linear2.bias"]:
																								UpperCamelCase_		:							Optional[int]  =		os.path.join(__UpperCamelCase			,     f'''{key}.dat'''						)
																								self.assertTrue(os.path.isfile(__UpperCamelCase						)						)
																								# TODO: add tests on the fact weights are properly loaded





						def        A_							(self						)				->				List[Any]:
												UpperCamelCase_		:							int  =		[torch.floataa, torch.floataa, torch.bfloataa]

												for dtype in dtypes:
																		UpperCamelCase_		:							List[str]  =		torch.randn(2			,     3			,     dtype=__UpperCamelCase						)
																		with TemporaryDirectory() as tmp_dir:
																								UpperCamelCase_		:							List[Any]  =		offload_weight(__UpperCamelCase			,     """weight"""			,     __UpperCamelCase			,     {}						)
																								UpperCamelCase_		:							List[Any]  =		os.path.join(__UpperCamelCase			,     """weight.dat"""						)
																								self.assertTrue(os.path.isfile(__UpperCamelCase						)						)
																								self.assertDictEqual(__UpperCamelCase			,     {"""weight""": {"""shape""": [2, 3], """dtype""": str(__UpperCamelCase						).split("""."""						)[1]}}						)

																								UpperCamelCase_		:							Dict  =		load_offloaded_weight(__UpperCamelCase			,     index["""weight"""]						)
																								self.assertTrue(torch.equal(__UpperCamelCase			,     __UpperCamelCase						)						)





						def        A_							(self						)				->				List[Any]:
												UpperCamelCase_		:							Optional[int]  =		ModelForTest()
												UpperCamelCase_		:							Union[str, Any]  =		model.state_dict()
												UpperCamelCase_		:							str  =		{k: v for k, v in state_dict.items() if """linear2""" not in k}
												UpperCamelCase_		:							Any  =		{k: v for k, v in state_dict.items() if """linear2""" in k}

												with TemporaryDirectory() as tmp_dir:
																		offload_state_dict(__UpperCamelCase			,     __UpperCamelCase						)
																		UpperCamelCase_		:							Union[str, Any]  =		OffloadedWeightsLoader(state_dict=__UpperCamelCase			,     save_folder=__UpperCamelCase						)

																		# Every key is there with the right value
																		self.assertEqual(sorted(__UpperCamelCase						)			,     sorted(state_dict.keys()						)						)
																		for key, param in state_dict.items():
																								self.assertTrue(torch.allclose(__UpperCamelCase			,     weight_map[key]						)						)

												UpperCamelCase_		:							int  =		{k: v for k, v in state_dict.items() if """weight""" in k}
												UpperCamelCase_		:							List[str]  =		{k: v for k, v in state_dict.items() if """weight""" not in k}

												with TemporaryDirectory() as tmp_dir:
																		offload_state_dict(__UpperCamelCase			,     __UpperCamelCase						)
																		UpperCamelCase_		:							str  =		OffloadedWeightsLoader(state_dict=__UpperCamelCase			,     save_folder=__UpperCamelCase						)

																		# Every key is there with the right value
																		self.assertEqual(sorted(__UpperCamelCase						)			,     sorted(state_dict.keys()						)						)
																		for key, param in state_dict.items():
																								self.assertTrue(torch.allclose(__UpperCamelCase			,     weight_map[key]						)						)

												with TemporaryDirectory() as tmp_dir:
																		offload_state_dict(__UpperCamelCase			,     __UpperCamelCase						)
																		# Duplicates are removed
																		UpperCamelCase_		:							Union[str, Any]  =		OffloadedWeightsLoader(state_dict=__UpperCamelCase			,     save_folder=__UpperCamelCase						)

																		# Every key is there with the right value
																		self.assertEqual(sorted(__UpperCamelCase						)			,     sorted(state_dict.keys()						)						)
																		for key, param in state_dict.items():
																								self.assertTrue(torch.allclose(__UpperCamelCase			,     weight_map[key]						)						)





						def        A_							(self						)				->				str:
												UpperCamelCase_		:							List[Any]  =		{"""a.1""": 0, """a.10""": 1, """a.2""": 2}
												UpperCamelCase_		:							Any  =		extract_submodules_state_dict(__UpperCamelCase			,     ["""a.1""", """a.2"""]						)
												self.assertDictEqual(__UpperCamelCase			,     {"""a.1""": 0, """a.2""": 2}						)

												UpperCamelCase_		:							Any  =		{"""a.1.a""": 0, """a.10.a""": 1, """a.2.a""": 2}
												UpperCamelCase_		:							Any  =		extract_submodules_state_dict(__UpperCamelCase			,     ["""a.1""", """a.2"""]						)
												self.assertDictEqual(__UpperCamelCase			,     {"""a.1.a""": 0, """a.2.a""": 2}						)







from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

SCREAMING_SNAKE_CASE		:     Union[str, Any]         =	{"UserAgent": UserAgent().random}






def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				Dict			):
						UpperCamelCase_		:							Tuple  =		script.contents[0]
						UpperCamelCase_		:							List[Any]  =		json.loads(data[data.find("""{\"config\""""			) : -1]			)
						return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]

class        UpperCamelCase						:





						def __init__(self			,     __UpperCamelCase						)				->				List[str]:
												UpperCamelCase_		:							Union[str, Any]  =		f'''https://www.instagram.com/{username}/'''
												UpperCamelCase_		:							Optional[int]  =		self.get_json()





						def        A_							(self						)				->				dict:
												UpperCamelCase_		:							Optional[Any]  =		requests.get(self.url			,     headers=__UpperCamelCase						).text
												UpperCamelCase_		:							Any  =		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						)				->				str:
												return f'''{self.__class__.__name__}(\'{self.username}\')'''





						def __str__(self						)				->				str:
												return f'''{self.fullname} ({self.username}) is {self.biography}'''





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





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





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





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





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





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





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





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





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





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





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






def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				str = "github"			):
						import os

						if os.environ.get("""CI"""			):
												return  # test failing on GitHub Actions
						UpperCamelCase_		:							Any  =		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 > 150
						assert instagram_user.number_of_followers > 12_0000
						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()
	SCREAMING_SNAKE_CASE		:     Dict         =	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 = }''')






