


import os
from datetime import datetime as dt

from github import Github


_A			=						[
    'good first issue',
    'feature request',
    'wip',
]

def 						_UpperCAmelCase    (      ):
     __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 SCREAMING_SNAKE_CASE__    : i.created_at      ,					reverse=SCREAMING_SNAKE_CASE__    )
          __UpperCamelCase   							=comments[0] if len(SCREAMING_SNAKE_CASE__    ) > 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()









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_A			=						{'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTConfig', 'ViTOnnxConfig']}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						['ViTFeatureExtractor']
   _A			=						['ViTImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'VIT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'ViTForImageClassification',
       'ViTForMaskedImageModeling',
       'ViTModel',
       'ViTPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'TFViTForImageClassification',
       'TFViTModel',
       'TFViTPreTrainedModel',
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A			=						[
       'FlaxViTForImageClassification',
       'FlaxViTModel',
       'FlaxViTPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_vit import ViTFeatureExtractor
      from .image_processing_vit import ViTImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vit import (
          VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
          ViTForImageClassification,
          ViTForMaskedImageModeling,
          ViTModel,
          ViTPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
   import sys

   _A			=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





