
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 	_lowerCAmelCase					(	unittest.TestCase       ):




				def      __a						(					self     )				->      str:
							# clean up the VRAM after each test
							super().tearDown()
							gc.collect()




				def      __a						(					self     )				->      List[Any]:
							lowerCAmelCase_						=	load_image(
							    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
							    "/sd2-inpaint/init_image.png"     )
							lowerCAmelCase_						=	load_image(
							    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd2-inpaint/mask.png"     )

							lowerCAmelCase_						=	"xvjiarui/stable-diffusion-2-inpainting"
							lowerCAmelCase_	,  lowerCAmelCase_						=	FlaxStableDiffusionInpaintPipeline.from_pretrained(_UpperCamelCase				,				safety_checker=_UpperCamelCase     )

							lowerCAmelCase_						=	"Face of a yellow cat, high resolution, sitting on a park bench"

							lowerCAmelCase_						=	jax.random.PRNGKey(0     )
							lowerCAmelCase_						=	50

							lowerCAmelCase_						=	jax.device_count()
							lowerCAmelCase_						=	num_samples * [prompt]
							lowerCAmelCase_						=	num_samples * [init_image]
							lowerCAmelCase_						=	num_samples * [mask_image]
							lowerCAmelCase_	,  lowerCAmelCase_	,  lowerCAmelCase_						=	pipeline.prepare_inputs(_UpperCamelCase				,				_UpperCamelCase				,				_UpperCamelCase     )

							# shard inputs and rng
							lowerCAmelCase_						=	replicate(_UpperCamelCase     )
							lowerCAmelCase_						=	jax.random.split(_UpperCamelCase				,				jax.device_count()     )
							lowerCAmelCase_						=	shard(_UpperCamelCase     )
							lowerCAmelCase_						=	shard(_UpperCamelCase     )
							lowerCAmelCase_						=	shard(_UpperCamelCase     )

							lowerCAmelCase_						=	pipeline(
							    _UpperCamelCase				,				_UpperCamelCase				,				_UpperCamelCase				,				_UpperCamelCase				,				_UpperCamelCase				,				_UpperCamelCase				,				jit=_UpperCamelCase     )

							lowerCAmelCase_						=	output.images.reshape(_UpperCamelCase				,				512				,				512				,				3     )

							lowerCAmelCase_						=	images[0, 253:256, 253:256, -1]

							lowerCAmelCase_						=	jnp.asarray(jax.device_get(image_slice.flatten()     )     )
							lowerCAmelCase_						=	jnp.array(
							    [0.3611307, 0.37649736, 0.3757408, 0.38213953, 0.39295167, 0.3841631, 0.41554978, 0.4137475, 0.4217084]     )
							print(f"""output_slice: {output_slice}"""     )
							assert jnp.abs(output_slice - expected_slice     ).max() < 1e-2





from pathlib import Path

import fire






def    lowerCamelCase__				(				__lowerCAmelCase  :  str    ,							__lowerCAmelCase  :  str    ,							__lowerCAmelCase  :  int				):




			"""simple docstring"""


			lowerCAmelCase_						=	Path(__lowerCAmelCase				)
			lowerCAmelCase_						=	Path(__lowerCAmelCase				)
			dest_dir.mkdir(exist_ok=__lowerCAmelCase				)
			for path in src_dir.iterdir():
						lowerCAmelCase_						=	[x.rstrip() for x in list(path.open().readlines()				)][:n]
						lowerCAmelCase_						=	dest_dir.joinpath(path.name				)
						print(__lowerCAmelCase				)
						dest_path.open("w"				).write("\n".join(__lowerCAmelCase				)				)


if __name__ == "__main__":
			fire.Fire(minify)



