



"""simple docstring"""

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        _UpperCAmelCase       (			unittest.TestCase):

 def 						_snake_case					(     self		:       List[str]				):
     # clean up the VRAM after each test
     super().tearDown()
     gc.collect()






 def 						_snake_case					(     self		:       int				):
     snake_case_ :     Optional[int]				=	load_image(
         '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
         '''/sd2-inpaint/init_image.png'''				)
     snake_case_ :     Tuple				=	load_image(
         '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png'''				)

     snake_case_ :     Any				=	'''xvjiarui/stable-diffusion-2-inpainting'''
     snake_case_,	snake_case_ :     Any				=	FlaxStableDiffusionInpaintPipeline.from_pretrained(lowercase_  ,     safety_checker=lowercase_				)

     snake_case_ :     Any				=	'''Face of a yellow cat, high resolution, sitting on a park bench'''

     snake_case_ :     Tuple				=	jax.random.PRNGKey(0				)
     snake_case_ :     Tuple				=	50

     snake_case_ :     Any				=	jax.device_count()
     snake_case_ :     Union[str, Any]				=	num_samples * [prompt]
     snake_case_ :     Optional[Any]				=	num_samples * [init_image]
     snake_case_ :     Dict				=	num_samples * [mask_image]
     snake_case_,	snake_case_,	snake_case_ :     List[Any]				=	pipeline.prepare_inputs(lowercase_  ,     lowercase_  ,     lowercase_				)

     # shard inputs and rng
     snake_case_ :     List[Any]				=	replicate(lowercase_				)
     snake_case_ :     Any				=	jax.random.split(lowercase_  ,     jax.device_count()				)
     snake_case_ :     Tuple				=	shard(lowercase_				)
     snake_case_ :     Union[str, Any]				=	shard(lowercase_				)
     snake_case_ :     Optional[int]				=	shard(lowercase_				)

     snake_case_ :     Optional[Any]				=	pipeline(
         lowercase_  ,     lowercase_  ,     lowercase_  ,     lowercase_  ,     lowercase_  ,     lowercase_  ,     jit=lowercase_				)

     snake_case_ :     Tuple				=	output.images.reshape(lowercase_  ,     512  ,     512  ,     3				)

     snake_case_ :     Tuple				=	images[0, 253:256, 253:256, -1]

     snake_case_ :     Optional[Any]				=	jnp.asarray(jax.device_get(image_slice.flatten()				)				)
     snake_case_ :     Union[str, Any]				=	jnp.array(
         [0.3_61_13_07, 0.37_64_97_36, 0.3_75_74_08, 0.38_21_39_53, 0.39_29_51_67, 0.3_84_16_31, 0.41_55_49_78, 0.4_13_74_75, 0.4_21_70_84]				)
     print(f"output_slice: {output_slice}"				)
     assert jnp.abs(output_slice - expected_slice				).max() < 1E-2










"""simple docstring"""

from functools import lru_cache




@lru_cache
def __lowercase			(							_a    ):
    if num < 0:
        raise ValueError('''Number should not be negative.'''    )

    return 1 if num in (0, 1) else num * factorial(num - 1    )


if __name__ == "__main__":
     import doctest

     doctest.testmod()





