



"""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  __SCREAMING_SNAKE_CASE			(   unittest.TestCase     ):


					'''simple docstring'''





					def 	snake_case ( self							:						List[Any]  )->      Tuple:
								# clean up the VRAM after each test
								super().tearDown()
								gc.collect()




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

								lowerCamelCase__	:	List[Any]				='''xvjiarui/stable-diffusion-2-inpainting'''
								lowerCamelCase__	:	Dict				=FlaxStableDiffusionInpaintPipeline.from_pretrained(UpperCamelCase__,						safety_checker=UpperCamelCase__  )

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

								lowerCamelCase__	:	List[str]				=jax.random.PRNGKey(0  )
								lowerCamelCase__	:	Dict				=50

								lowerCamelCase__	:	Any				=jax.device_count()
								lowerCamelCase__	:	str				=num_samples * [prompt]
								lowerCamelCase__	:	int				=num_samples * [init_image]
								lowerCamelCase__	:	Tuple				=num_samples * [mask_image]
								lowerCamelCase__	:	int				=pipeline.prepare_inputs(UpperCamelCase__,						UpperCamelCase__,						UpperCamelCase__  )

								# shard inputs and rng
								lowerCamelCase__	:	Optional[Any]				=replicate(UpperCamelCase__  )
								lowerCamelCase__	:	Any				=jax.random.split(UpperCamelCase__,						jax.device_count()  )
								lowerCamelCase__	:	Any				=shard(UpperCamelCase__  )
								lowerCamelCase__	:	Optional[int]				=shard(UpperCamelCase__  )
								lowerCamelCase__	:	Union[str, Any]				=shard(UpperCamelCase__  )

								lowerCamelCase__	:	int				=pipeline(
								    UpperCamelCase__,						UpperCamelCase__,						UpperCamelCase__,						UpperCamelCase__,						UpperCamelCase__,						UpperCamelCase__,						jit=UpperCamelCase__  )

								lowerCamelCase__	:	int				=output.images.reshape(UpperCamelCase__,						512,						512,						3  )

								lowerCamelCase__	:	Union[str, Any]				=images[0, 253:256, 253:256, -1]

								lowerCamelCase__	:	Dict				=jnp.asarray(jax.device_get(image_slice.flatten()  )  )
								lowerCamelCase__	:	Union[str, Any]				=jnp.array(
								    [0.3_611_307, 0.37_649_736, 0.3_757_408, 0.38_213_953, 0.39_295_167, 0.3_841_631, 0.41_554_978, 0.4_137_475, 0.4_217_084]  )
								print(F'''output_slice: {output_slice}'''  )
								assert jnp.abs(output_slice - expected_slice  ).max() < 1E-2









"""simple docstring"""






from ..utils import DummyObject, requires_backends

class  __SCREAMING_SNAKE_CASE			(   metaclass=lowerCAmelCase_     ):


					'''simple docstring'''





					_a         =							['onnx']



					def __init__( self							:						List[str],						*lowerCamelCase							:						Union[str, Any],						**lowerCamelCase							:						str  )->      Optional[int]:
								requires_backends(self,						['''onnx''']  )



					@classmethod
					def 	snake_case ( cls							:						List[str],						*lowerCamelCase							:						Any,						**lowerCamelCase							:						Union[str, Any]  )->      Optional[int]:
								requires_backends(cls,						['''onnx''']  )




					@classmethod
					def 	snake_case ( cls							:						Union[str, Any],						*lowerCamelCase							:						Tuple,						**lowerCamelCase							:						Tuple  )->      Optional[int]:
								requires_backends(cls,						['''onnx''']  )




