"""simple docstring"""



from datetime import datetime as dt
import os

from github import Github


__lowercase		:		List[str]														=							[
    "good first issue",
    "good second issue",
    "good difficult issue",
    "feature request",
    "new model",
    "wip",
]





def    SCREAMING_SNAKE_CASE       (     ):
     __snake_case				=							Github(os.environ['''GITHUB_TOKEN'''])
     __snake_case				=							g.get_repo('''huggingface/transformers''')
     __snake_case				=							repo.get_issues(state='''open''')

     for issue in open_issues:
          __snake_case				=							sorted([comment for comment in issue.get_comments()],      key=lambda snake_case: i.created_at,      reverse=snake_case)
          __snake_case				=							comments[0] if len(snake_case) > 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()
"""simple docstring"""



from typing import TYPE_CHECKING

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


__lowercase		:		Dict														=							{
    "configuration_vision_text_dual_encoder": ["VisionTextDualEncoderConfig"],
    "processing_vision_text_dual_encoder": ["VisionTextDualEncoderProcessor"],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase		:		Optional[int]														=							["VisionTextDualEncoderModel"]


try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase		:		Optional[int]														=							["FlaxVisionTextDualEncoderModel"]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase		:		Any														=							["TFVisionTextDualEncoderModel"]


if TYPE_CHECKING:
       from .configuration_vision_text_dual_encoder import VisionTextDualEncoderConfig
       from .processing_vision_text_dual_encoder import VisionTextDualEncoderProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_vision_text_dual_encoder import VisionTextDualEncoderModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_vision_text_dual_encoder import FlaxVisionTextDualEncoderModel

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_vision_text_dual_encoder import TFVisionTextDualEncoderModel


else:
       import sys

       __lowercase		:		Tuple														=							_LazyModule(__name__, globals()["__file__"], _import_structure)