


import os
from datetime import datetime as dt

from github import Github


__UpperCamelCase     		=							[
    "good first issue",
    "feature request",
    "wip",
]
def 							UpperCamelCase_(					)->		Optional[Any]:
			UpperCamelCase__       =							Github(os.environ["GITHUB_TOKEN"]	)
			UpperCamelCase__       =							g.get_repo("huggingface/accelerate"	)
			UpperCamelCase__       =							repo.get_issues(state="open"	)

			for issue in open_issues:
						UpperCamelCase__       =							sorted([comment for comment in issue.get_comments()]					,  key=lambda _A	: i.created_at					,  reverse=A__	)
						UpperCamelCase__       =							comments[0] if len(A__	) > 0 else None
						UpperCamelCase__       =							dt.utcnow()
						UpperCamelCase__       =							(current_time - issue.updated_at).days
						UpperCamelCase__       =							(current_time - issue.created_at).days
						if (
						    last_comment is not None
						    and last_comment.user.login == "github-actions[bot]"
						    and days_since_updated > 7
						    and days_since_creation >= 30
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()	)
						):
									# Close issue since it has been 7 days of inactivity since bot mention.
									issue.edit(state="closed"	)
						elif (
						    days_since_updated > 23
						    and days_since_creation >= 30
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()	)
						):
									# Add stale comment
									issue.create_comment(
									    "This issue has been automatically marked as stale because it has not had "
									    "recent activity. If you think this still needs to be addressed "
									    "please comment on this thread.\n\nPlease note that issues that do not follow the "
									    "[contributing guidelines](https://github.com/huggingface/accelerate/blob/main/CONTRIBUTING.md) "
									    "are likely to be ignored."	)


if __name__ == "__main__":
						main()






'''simple docstring'''






from typing import Union

import fire
import torch
from tqdm import tqdm







def 							UpperCamelCase_     (       A__   :  str				,       A__   :  str = "cpu"				,       A__   :  Union[str, None] = None   ):
  '''simple docstring'''





  lowerCAmelCase_     : Dict     =  torch.load(A__				,       map_location=A__   )
  for k, v in tqdm(state_dict.items()   ):
    if not isinstance(A__				,       torch.Tensor   ):
      raise TypeError("""FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"""   )
    lowerCAmelCase_     : List[str]     =  v.half()
  if save_path is None:  # overwrite src_path
    lowerCAmelCase_     : List[str]     =  src_path
  torch.save(A__				,       A__   )


if __name__ == "__main__":
  fire.Fire(convert)



