'''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        __A      ( unittest.TestCase	):



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






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

         UpperCAmelCase_           =   '''xvjiarui/stable-diffusion-2-inpainting'''
         UpperCAmelCase_           =   FlaxStableDiffusionInpaintPipeline.from_pretrained(A_   ,			safety_checker=A_ )

         UpperCAmelCase_           =   '''Face of a yellow cat, high resolution, sitting on a park bench'''

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

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

         # shard inputs and rng
         UpperCAmelCase_           =   replicate(A_ )
         UpperCAmelCase_           =   jax.random.split(A_   ,			jax.device_count() )
         UpperCAmelCase_           =   shard(A_ )
         UpperCAmelCase_           =   shard(A_ )
         UpperCAmelCase_           =   shard(A_ )

         UpperCAmelCase_           =   pipeline(
             A_   ,			A_   ,			A_   ,			A_   ,			A_   ,			A_   ,			jit=A_ )

         UpperCAmelCase_           =   output.images.reshape(A_   ,			512   ,			512   ,			3 )

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

         UpperCAmelCase_           =   jnp.asarray(jax.device_get(image_slice.flatten() ) )
         UpperCAmelCase_           =   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









import string


def 			UpperCamelCase(  __UpperCamelCase							:		str ):
		for key in range(len(string.ascii_uppercase ) ):
				lowerCAmelCase_			:     List[Any]									= ''''''
				for symbol in message:
						if symbol in string.ascii_uppercase:
								lowerCAmelCase_			:     Optional[int]									= string.ascii_uppercase.find(__UpperCamelCase )
								lowerCAmelCase_			:     Optional[int]									= num - key
								if num < 0:
										lowerCAmelCase_			:     int									= num + len(string.ascii_uppercase )
								lowerCAmelCase_			:     int									= translated + string.ascii_uppercase[num]
						else:
								lowerCAmelCase_			:     Optional[int]									= translated + symbol
				print(f"""Decryption using Key #{key}: {translated}""" )


def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     Dict									= input('''Encrypted message: ''' )
		lowerCAmelCase_			:     List[str]									= message.upper()
		decrypt(__UpperCamelCase )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()





