


'''simple docstring'''






import os
from datetime import datetime as dt

from github import Github


lowercase				=[
    'good first issue',
    'good second issue',
    'good difficult issue',
    'enhancement',
    'new pipeline/model',
    'new scheduler',
    'wip',
]





def lowerCamelCase__     (		):







   '''simple docstring'''




   _UpperCAmelCase  :  Dict				       =Github(os.environ['GITHUB_TOKEN']				)
   _UpperCAmelCase  :  Tuple				       =g.get_repo('huggingface/diffusers'				)
   _UpperCAmelCase  :  str				       =repo.get_issues(state='open'				)

   for issue in open_issues:
      _UpperCAmelCase  :  List[Any]				       =sorted(issue.get_comments()			,       key=lambda __lowerCamelCase				: i.created_at			,       reverse=__lowerCamelCase				)
      _UpperCAmelCase  :  Any				       =comments[0] if len(__lowerCamelCase				) > 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 >= 3_0
          and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()				)
      ):
         # Closes the issue after 7 days of inactivity since the Stalebot notification.
         issue.edit(state='closed'				)
      elif (
          "stale" in issue.get_labels()
          and last_comment is not None
          and last_comment.user.login != "github-actions[bot]"
      ):
         # Opens the issue if someone other than Stalebot commented.
         issue.edit(state='open'				)
         issue.remove_from_labels('stale'				)
      elif (
          (dt.utcnow() - issue.updated_at).days > 2_3
          and (dt.utcnow() - issue.created_at).days >= 3_0
          and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()				)
      ):
         # Post a Stalebot notification after 23 days of inactivity.
         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/diffusers/blob/main/CONTRIBUTING.md) '
             'are likely to be ignored.'				)
         issue.add_to_labels('stale'				)


if __name__ == "__main__":
 main()





'''simple docstring'''






from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
 from PIL import Image

 from ..image_utils import load_image

if is_tf_available():
 import tensorflow as tf

 from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
 from ..tf_utils import stable_softmax

if is_torch_available():
 from ..models.auto.modeling_auto import MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING

lowercase				=logging.get_logger(__name__)






@add_end_docstrings(lowerCAmelCase							)
class    __magic_name__				(						lowerCAmelCase							):






       def __init__(     self    ,				*snake_case    ,				**snake_case)		->    Dict:




          '''simple docstring'''
          super().__init__(*snake_case    ,				**snake_case)
          requires_backends(self    ,				'vision')
          self.check_model_type(
              TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
              if self.framework == 'tf'
              else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING)






       def      lowerCAmelCase						(     self    ,				snake_case=None)		->    str:




          '''simple docstring'''
          _UpperCAmelCase  :  Any				       ={}
          if top_k is not None:
             _UpperCAmelCase  :  Optional[int]				       =top_k
          return {}, {}, postprocess_params






       def __call__(     self    ,				snake_case    ,				**snake_case)		->    List[str]:




          '''simple docstring'''
          return super().__call__(snake_case    ,				**snake_case)






       def      lowerCAmelCase						(     self    ,				snake_case)		->    List[str]:




          '''simple docstring'''
          _UpperCAmelCase  :  int				       =load_image(snake_case)
          _UpperCAmelCase  :  Tuple				       =self.image_processor(images=snake_case    ,				return_tensors=self.framework)
          return model_inputs






       def      lowerCAmelCase						(     self    ,				snake_case)		->    Optional[Any]:




          '''simple docstring'''
          _UpperCAmelCase  :  List[str]				       =self.model(**snake_case)
          return model_outputs






       def      lowerCAmelCase						(     self    ,				snake_case    ,				snake_case=5)		->    Any:




          '''simple docstring'''
          if top_k > self.model.config.num_labels:
             _UpperCAmelCase  :  Optional[Any]				       =self.model.config.num_labels

          if self.framework == "pt":
             _UpperCAmelCase  :  List[Any]				       =model_outputs.logits.softmax(-1)[0]
             _UpperCAmelCase       ,			_UpperCAmelCase  :  Optional[Any]				       =probs.topk(snake_case)
          elif self.framework == "tf":
             _UpperCAmelCase  :  int				       =stable_softmax(model_outputs.logits    ,				axis=-1)[0]
             _UpperCAmelCase  :  List[Any]				       =tf.math.top_k(snake_case    ,				k=snake_case)
             _UpperCAmelCase       ,			_UpperCAmelCase  :  List[str]				       =topk.values.numpy(), topk.indices.numpy()
          else:
             raise ValueError(f"Unsupported framework: {self.framework}")

          _UpperCAmelCase  :  int				       =scores.tolist()
          _UpperCAmelCase  :  Tuple				       =ids.tolist()
          return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(snake_case    ,				snake_case)]

