


import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
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     _lowercase				(							lowercase__							,						lowercase__							,						unittest.TestCase):


       """simple docstring"""




       A__      		=    IFInpaintingSuperResolutionPipeline
       A__      		=    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"width", "height"}
       A__      		=    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({"original_image"})
       A__      		=    PipelineTesterMixin.required_optional_params - {"latents"}





       def 		lowerCAmelCase  (     self							:    Optional[int] ):


             '''simple docstring'''



             return self._get_superresolution_dummy_components()





       def 		lowerCAmelCase  (     self							:    Optional[Any]      ,   __lowerCamelCase							:    Dict      ,   __lowerCamelCase							:    List[Any]=0 ):


             '''simple docstring'''



             if str(__lowerCamelCase ).startswith("mps" ):
                   lowerCamelCase__	:       str					=						torch.manual_seed(__lowerCamelCase )
             else:
                   lowerCamelCase__	:       Dict					=						torch.Generator(device=__lowerCamelCase ).manual_seed(__lowerCamelCase )

             lowerCamelCase__	:       Optional[int]					=						floats_tensor((1, 3, 16, 16)      ,   rng=random.Random(__lowerCamelCase ) ).to(__lowerCamelCase )
             lowerCamelCase__	:       int					=						floats_tensor((1, 3, 32, 32)      ,   rng=random.Random(__lowerCamelCase ) ).to(__lowerCamelCase )
             lowerCamelCase__	:       Tuple					=						floats_tensor((1, 3, 32, 32)      ,   rng=random.Random(__lowerCamelCase ) ).to(__lowerCamelCase )

             lowerCamelCase__	:       Any					=						{
                 "prompt": "A painting of a squirrel eating a burger",
                 "image": image,
                 "original_image": original_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 		lowerCAmelCase  (     self							:    Optional[int] ):


             '''simple docstring'''



             self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3 )





       def 		lowerCAmelCase  (     self							:    Dict ):


             '''simple docstring'''



             self._test_save_load_optional_components()





       @unittest.skipIf(torch_device != "cuda"      ,   reason="float16 requires CUDA" )
       def 		lowerCAmelCase  (     self							:    Any ):


             '''simple docstring'''



             super().test_save_load_floataa(expected_max_diff=1E-1 )





       def 		lowerCAmelCase  (     self							:    Optional[int] ):


             '''simple docstring'''



             self._test_attention_slicing_forward_pass(expected_max_diff=1E-2 )





       def 		lowerCAmelCase  (     self							:    int ):


             '''simple docstring'''



             self._test_save_load_local()





       def 		lowerCAmelCase  (     self							:    Optional[int] ):


             '''simple docstring'''



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






import os
from datetime import datetime as dt

from github import Github


A   :					Union[str, Any]	=      [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "enhancement",
    "new pipeline/model",
    "new scheduler",
    "wip",
]

def    lowercase_	(	):

      """simple docstring"""




      lowerCamelCase__	:       Optional[int]					=						Github(os.environ["GITHUB_TOKEN"]		)
      lowerCamelCase__	:       str					=						g.get_repo("huggingface/diffusers"		)
      lowerCamelCase__	:       Optional[int]					=						repo.get_issues(state="open"		)

      for issue in open_issues:
            lowerCamelCase__	:       str					=						sorted(issue.get_comments()					,      key=lambda _A		: i.created_at					,      reverse=_A		)
            lowerCamelCase__	:       str					=						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()		)
            ):
                  # 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()


