from datetime import datetime as dt
import os

from github import Github


__magic_name__								=[
    '''good first issue''',
    '''good second issue''',
    '''good difficult issue''',
    '''feature request''',
    '''new model''',
    '''wip''',
]







def  __UpperCamelCase    (						):
     UpperCamelCase__										=      Github(os.environ['''GITHUB_TOKEN''']							)
     UpperCamelCase__										=      g.get_repo('''huggingface/transformers'''							)
     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
          if (
              last_comment is not None
              and last_comment.user.login == "github-actions[bot]"
              and (dt.utcnow() - issue.updated_at).days > 7
              and (dt.utcnow() - issue.created_at).days >= 30
              and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()							)
          ):
               # print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
               issue.edit(state='''closed'''							)
          elif (
              (dt.utcnow() - issue.updated_at).days > 23
              and (dt.utcnow() - issue.created_at).days >= 30
              and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()							)
          ):
               # print(f"Would add stale comment to {issue.number}")
               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/transformers/blob/main/CONTRIBUTING.md) '''
                   '''are likely to be ignored.'''							)


if __name__ == "__main__":
     main()




from typing import Optional, Union

import torch
from torch import nn

from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin



class     _A   (    __UpperCamelCase	, __UpperCamelCase							):






  @register_to_config
  def __init__(self   ,				SCREAMING_SNAKE_CASE_ = 768   ,				)		->      Tuple:





       '''simple docstring'''





       super().__init__()

       UpperCamelCase__										=      nn.Parameter(torch.zeros(1   ,				SCREAMING_SNAKE_CASE_	)	)
       UpperCamelCase__										=      nn.Parameter(torch.ones(1   ,				SCREAMING_SNAKE_CASE_	)	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_ = None   ,				SCREAMING_SNAKE_CASE_ = None   ,				)		->      Tuple:





       '''simple docstring'''





       UpperCamelCase__										=      nn.Parameter(self.mean.to(SCREAMING_SNAKE_CASE_	).to(SCREAMING_SNAKE_CASE_	)	)
       UpperCamelCase__										=      nn.Parameter(self.std.to(SCREAMING_SNAKE_CASE_	).to(SCREAMING_SNAKE_CASE_	)	)
       return self






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      int:





       '''simple docstring'''





       UpperCamelCase__										=      (embeds - self.mean) * 1.0 / self.std
       return embeds






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      int:





       '''simple docstring'''





       UpperCamelCase__										=      (embeds * self.std) + self.mean
       return embeds



