


import gc
import unittest

from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
       import jax
       import jax.numpy as jnp
       from flax.jax_utils import replicate
       from flax.training.common_utils import shard


@slow
@require_flax
class   a__	(						unittest.TestCase    ):

       def 						UpperCAmelCase(   self      :     Tuple    ):
            # clean up the VRAM after each test
            super().tearDown()
            gc.collect()

       def 						UpperCAmelCase(   self      :     Optional[Any]    ):
            a_    :     Any										=    load_image(
                """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
                """/sd2-inpaint/init_image.png"""    )
            a_    :     int										=    load_image(
                """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png"""    )

            a_    :     Optional[Any]										=    """xvjiarui/stable-diffusion-2-inpainting"""
            a_			,			a_    :     List[Any]										=    FlaxStableDiffusionInpaintPipeline.from_pretrained(lowerCamelCase_      ,							safety_checker=lowerCamelCase_    )

            a_    :     Union[str, Any]										=    """Face of a yellow cat, high resolution, sitting on a park bench"""

            a_    :     str										=    jax.random.PRNGKey(0    )
            a_    :     int										=    5_0

            a_    :     List[str]										=    jax.device_count()
            a_    :     Optional[int]										=    num_samples * [prompt]
            a_    :     Optional[int]										=    num_samples * [init_image]
            a_    :     Tuple										=    num_samples * [mask_image]
            a_			,			a_			,			a_    :     int										=    pipeline.prepare_inputs(lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_    )

            # shard inputs and rng
            a_    :     Optional[Any]										=    replicate(lowerCamelCase_    )
            a_    :     Any										=    jax.random.split(lowerCamelCase_      ,							jax.device_count()    )
            a_    :     List[Any]										=    shard(lowerCamelCase_    )
            a_    :     List[str]										=    shard(lowerCamelCase_    )
            a_    :     str										=    shard(lowerCamelCase_    )

            a_    :     int										=    pipeline(
                lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_      ,							lowerCamelCase_      ,							jit=lowerCamelCase_    )

            a_    :     Dict										=    output.images.reshape(lowerCamelCase_      ,							5_1_2      ,							5_1_2      ,							3    )

            a_    :     List[Any]										=    images[0, 2_5_3:2_5_6, 2_5_3:2_5_6, -1]

            a_    :     List[str]										=    jnp.asarray(jax.device_get(image_slice.flatten()    )    )
            a_    :     Any										=    jnp.array(
                [0.3_6_1_1_3_0_7, 0.3_7_6_4_9_7_3_6, 0.3_7_5_7_4_0_8, 0.3_8_2_1_3_9_5_3, 0.3_9_2_9_5_1_6_7, 0.3_8_4_1_6_3_1, 0.4_1_5_5_4_9_7_8, 0.4_1_3_7_4_7_5, 0.4_2_1_7_0_8_4]    )
            print(F'''output_slice: {output_slice}'''    )
            assert jnp.abs(output_slice - expected_slice    ).max() < 1E-2







from datetime import datetime as dt
import os

from github import Github


__lowerCamelCase        =     [
    '''good first issue''',
    '''good second issue''',
    '''good difficult issue''',
    '''feature request''',
    '''new model''',
    '''wip''',
]



def  _a			(						):
     a_    :     List[str]										=    Github(os.environ["""GITHUB_TOKEN"""] )
     a_    :     str										=    g.get_repo("""huggingface/transformers""" )
     a_    :     List[str]										=    repo.get_issues(state="""open""" )

     for issue in open_issues:
          a_    :     Optional[Any]										=    sorted([comment for comment in issue.get_comments()]  ,  key=lambda __UpperCamelCase : i.created_at  ,  reverse=__UpperCamelCase )
          a_    :     List[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 >= 3_0
              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 > 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() )
          ):
               # 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()



