
"""simple docstring"""




import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin


@skip_mps
class       __magic_name__							(							SCREAMING_SNAKE_CASE__ ,       SCREAMING_SNAKE_CASE__ ,       unittest.TestCase			):
       UpperCamelCase_ =		IFInpaintingPipeline
       UpperCamelCase_ =		TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'''width''', '''height'''}
       UpperCamelCase_ =		TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
       UpperCamelCase_ =		PipelineTesterMixin.required_optional_params - {'''latents'''}
       def 				lowercase_				(  self							)  ->						Any:





         """simple docstring"""




         return self._get_dummy_components()
       def 				lowercase_				(  self			,					A_			,					A_=0							)  ->						Union[str, Any]:





         """simple docstring"""




         if str(A_							).startswith('''mps'''							):
           _lowercase:      str   			=  torch.manual_seed(A_							)
         else:
           _lowercase:      List[Any]   			=  torch.Generator(device=A_							).manual_seed(A_							)

         _lowercase:      Union[str, Any]   			=  floats_tensor((1, 3, 32, 32)			,					rng=random.Random(A_							)							).to(A_							)
         _lowercase:      Union[str, Any]   			=  floats_tensor((1, 3, 32, 32)			,					rng=random.Random(A_							)							).to(A_							)

         _lowercase:      Union[str, Any]   			=  {
             '''prompt''': '''A painting of a squirrel eating a burger''',
             '''image''': image,
             '''mask_image''': mask_image,
             '''generator''': generator,
             '''num_inference_steps''': 2,
             '''output_type''': '''numpy''',
         }

         return inputs
       @unittest.skipIf(
           torch_device != '''cuda''' or not is_xformers_available()			,					reason='''XFormers attention is only available with CUDA and `xformers` installed'''			,					)
       def 				lowercase_				(  self							)  ->						Union[str, Any]:





         """simple docstring"""




         self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3							)
       def 				lowercase_				(  self							)  ->						Tuple:





         """simple docstring"""




         self._test_save_load_optional_components()
       @unittest.skipIf(torch_device != '''cuda'''			,					reason='''float16 requires CUDA'''							)
       def 				lowercase_				(  self							)  ->						int:





         """simple docstring"""




         super().test_save_load_floataa(expected_max_diff=1E-1							)
       def 				lowercase_				(  self							)  ->						Union[str, Any]:





         """simple docstring"""




         self._test_attention_slicing_forward_pass(expected_max_diff=1E-2							)
       def 				lowercase_				(  self							)  ->						List[str]:





         """simple docstring"""




         self._test_save_load_local()



       def 				lowercase_				(  self							)  ->						Dict:





         """simple docstring"""




         self._test_inference_batch_single_identical(
             expected_max_diff=1E-2			,					)


"""simple docstring"""




import os
from datetime import datetime as dt

from github import Github


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




def 			_lowerCAmelCase		(		):






  """simple docstring"""



  _lowercase:      Optional[int]   			=  Github(os.environ['''GITHUB_TOKEN''']    )
  _lowercase:      Optional[int]   			=  g.get_repo('''huggingface/diffusers'''    )
  _lowercase:      Union[str, Any]   			=  repo.get_issues(state='''open'''    )

  for issue in open_issues:
    _lowercase:      List[Any]   			=  sorted(issue.get_comments()			,					key=lambda _UpperCamelCase    : i.created_at			,					reverse=_UpperCamelCase    )
    _lowercase:      Optional[Any]   			=  comments[0] if len(_UpperCamelCase    ) > 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()    )
    ):
      # 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 > 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()    )
    ):
      # 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()
