"""simple docstring"""






import re



def 						a_		(      lowerCamelCase ):
				return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]'      ,    str_ )]



def 						a_		(      lowerCamelCase ):
				UpperCAmelCase__    =							split_input(str_ )
				return "".join(
				    [''.join([char.capitalize() for char in sub_str] ) for sub_str in string_split] )



def 						a_		(      lowerCamelCase      ,    lowerCamelCase      ,    lowerCamelCase ):
				try:
								UpperCAmelCase__    =							split_input(lowerCamelCase )
								if upper:
												UpperCAmelCase__    =							''.join(
												    [
												        separator.join([char.upper() for char in sub_str] )
												        for sub_str in string_split
												    ] )
								else:
												UpperCAmelCase__    =							''.join(
												    [
												        separator.join([char.lower() for char in sub_str] )
												        for sub_str in string_split
												    ] )
								return res_str
				except IndexError:
								return "not valid string"



def 						a_		(      lowerCamelCase ):
				return to_simple_case(lowerCamelCase )



def 						a_		(      lowerCamelCase ):
				try:
								UpperCAmelCase__    =							to_simple_case(lowerCamelCase )
								return res_str[0].lower() + res_str[1:]
				except IndexError:
								return "not valid string"



def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				return to_complex_case(lowerCamelCase      ,    lowerCamelCase      ,    '_' )



def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				return to_complex_case(lowerCamelCase      ,    lowerCamelCase      ,    '-' )


if __name__ == "__main__":
						__import__('doctest').testmod()




"""simple docstring"""






import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


lowerCAmelCase__						:						Optional[int]		  =			False
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					pass






@slow
@require_torch_gpu
class        snake_case (				unittest.TestCase       ):




					"""simple docstring"""

					def 	__lowerCAmelCase		(       self     :			Tuple    ):
									UpperCAmelCase__    =							VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion'    )
									pipe.to(lowerCamelCase__    )
									pipe.set_progress_bar_config(disable=lowerCamelCase__    )

									UpperCAmelCase__    =							load_image(
									    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'    )
									UpperCAmelCase__    =							torch.manual_seed(0    )
									UpperCAmelCase__    =							pipe(
									    image=lowerCamelCase__					,generator=lowerCamelCase__					,guidance_scale=7.5					,num_inference_steps=50					,output_type='numpy'					,).images

									UpperCAmelCase__    =							image[0, 253:256, 253:256, -1]

									assert image.shape == (1, 512, 512, 3)
									UpperCAmelCase__    =							np.array([0.0_4_4_1, 0.0_4_6_9, 0.0_5_0_7, 0.0_5_7_5, 0.0_6_3_2, 0.0_6_5_0, 0.0_8_6_5, 0.0_9_0_9, 0.0_9_4_5]    )

									assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-2



