"""simple docstring"""
from __future__ import annotations

import requests

SCREAMING_SNAKE_CASE__      =					set(
    "approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\nedited gilded gildings hidden hide_score is_created_from_ads_ui is_meta\nis_original_content is_reddit_media_domain is_video link_flair_css_class\nlink_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title\nname permalink pwls quarantine saved score secure_media secure_media_embed selftext\nsubreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type\ntotal_awards_received ups upvote_ratio url user_reports".split()
)





def 				lowerCAmelCase__      (     _UpperCamelCase    :			str	,     _UpperCamelCase    :			Optional[Any] = 1	,     _UpperCamelCase    :			Optional[int] = "new"	,     _UpperCamelCase    :			Optional[int] = None   )   ->			List[str]:





						"""simple docstring"""






						snake_case        =     wanted_data or []
						if invalid_search_terms := ", ".join(sorted(set(_lowercase   ) - valid_terms   )   ):
												snake_case        =     f"""Invalid search term: {invalid_search_terms}"""
												raise ValueError(_lowercase   )
						snake_case        =     requests.get(
						    f"""https://reddit.com/r/{subreddit}/{age}.json?limit={limit}"""	,     headers={'User-agent': 'A random string'}	,     )
						if response.status_code == 4_2_9:
												raise requests.HTTPError

						snake_case        =     response.json()
						if not wanted_data:
												return {id_: data["data"]["children"][id_] for id_ in range(_lowercase   )}

						snake_case        =     {}
						for id_ in range(_lowercase   ):
												snake_case        =     {
												    item: data['data']['children'][id_]['data'][item] for item in wanted_data
												}
						return data_dict


if __name__ == "__main__":
					# If you get Error 429, that means you are rate limited.Try after some time
					print(get_subreddit_data("learnpython", wanted_data=["title", "url", "selftext"]))



"""simple docstring"""
import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu



@require_cpu
class 					lowerCAmelCase_      (     unittest.TestCase   ):



				"""simple docstring"""

				def 						snake_case	(			self      ):






										"""simple docstring"""

										snake_case        =     torch.nn.Linear(10						,      10      )
										snake_case        =     torch.optim.SGD(model.parameters()						,      0.1      )
										snake_case        =     Accelerator()
										snake_case        =     accelerator.prepare(lowerCAmelCase      )
										try:
																pickle.loads(pickle.dumps(lowerCAmelCase      )      )
										except Exception as e:
																self.fail(F"""Accelerated optimizer pickling failed with {e}"""      )
										AcceleratorState._reset_state()


