


'''simple docstring'''






import math


def       _snake_case     (  A				,					A )		->					int:
							lowerCAmelCase__      =			len(A )
							lowerCAmelCase__      =			int(math.floor(math.sqrt(A ) ) )
							lowerCAmelCase__      =			0
							while arr[min(A				,					A ) - 1] < x:
														lowerCAmelCase__      =			step
														step += int(math.floor(math.sqrt(A ) ) )
														if prev >= n:
																					return -1

							while arr[prev] < x:
														lowerCAmelCase__      =			prev + 1
														if prev == min(A				,					A ):
																					return -1
							if arr[prev] == x:
														return prev
							return -1


if __name__ == "__main__":
		__UpperCAmelCase					       =							input('''Enter numbers separated by a comma:\n''').strip()
		__UpperCAmelCase					       =							[int(item) for item in user_input.split(''',''')]
		__UpperCAmelCase					       =							int(input('''Enter the number to be searched:\n'''))
		__UpperCAmelCase					       =							jump_search(arr, x)
		if res == -1:
				print('''Number not found!''')
		else:
				print(f"""Number {x} is at index {res}""")



'''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


__UpperCAmelCase					       =							False




class 	a__       (							unittest.TestCase						):





							'''simple docstring'''






							pass




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





							'''simple docstring'''






							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							str:
														lowerCAmelCase__      =			VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''     )
														pipe.to(lowerCamelCase_     )
														pipe.set_progress_bar_config(disable=lowerCamelCase_     )

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

														lowerCAmelCase__      =			image[0, 2_53:2_56, 2_53:2_56, -1]

														assert image.shape == (1, 5_12, 5_12, 3)
														lowerCAmelCase__      =			np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]     )

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