






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


UpperCamelCase        =				False

class        lowerCAmelCase_				(      unittest.TestCase	):







				"""simple docstring"""




				pass

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







				"""simple docstring"""




				def 				__a   ( self     :Optional[int]     ):
					UpperCamelCase__ :Optional[Any]						=      VersatileDiffusionImageVariationPipeline.from_pretrained("""shi-labs/versatile-diffusion"""     )
					pipe.to(lowerCamelCase__     )
					pipe.set_progress_bar_config(disable=lowerCamelCase__     )

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

					UpperCamelCase__ :Optional[int]						=      image[0, 2_53:2_56, 2_53:2_56, -1]

					assert image.shape == (1, 5_12, 5_12, 3)
					UpperCamelCase__ :Any						=      np.array([0.0441, 0.0469, 0.0507, 0.0575, 0.0632, 0.0650, 0.0865, 0.0909, 0.0945]     )

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






"""simple docstring"""


import math

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						return math.pow(SCREAMING_SNAKE_CASE							,     2     ) - a

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return 2 * x

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Union[str, Any]				   =			2.0

						while start <= a:
												UpperCamelCase				:		Optional[Any]				   =			math.pow(SCREAMING_SNAKE_CASE							,     2     )

						return start

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE = 9999							,     SCREAMING_SNAKE_CASE = 0.00_00_00_00_00_00_01     ):

						if a < 0:
												raise ValueError("""math domain error"""     )

						UpperCamelCase				:		Optional[Any]				   =			get_initial_point(SCREAMING_SNAKE_CASE     )

						for _ in range(SCREAMING_SNAKE_CASE     ):
												UpperCamelCase				:		List[str]				   =			value
												UpperCamelCase				:		Tuple				   =			value - fx(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ) / fx_derivative(SCREAMING_SNAKE_CASE     )
												if abs(prev_value - value     ) < tolerance:
																		return value

						return value


if __name__ == "__main__":
		from doctest import testmod

		testmod()



