


'''simple docstring'''






def       _snake_case     (  A				,					A )		->					List[Any]:
							lowerCAmelCase__      =			0
							lowerCAmelCase__      =			len(A ) - 1

							while left <= right:
														# avoid divided by 0 during interpolation
														if sorted_collection[left] == sorted_collection[right]:
																					if sorted_collection[left] == item:
																												return left
																					else:
																												return None

														lowerCAmelCase__      =			left + ((item - sorted_collection[left]) * (right - left)) // (
														    sorted_collection[right] - sorted_collection[left]
														)

														# out of range check
														if point < 0 or point >= len(A ):
																					return None

														lowerCAmelCase__      =			sorted_collection[point]
														if current_item == item:
																					return point
														else:
																					if point < left:
																												lowerCAmelCase__      =			left
																												lowerCAmelCase__      =			point
																					elif point > right:
																												lowerCAmelCase__      =			right
																												lowerCAmelCase__      =			point
																					else:
																												if item < current_item:
																																			lowerCAmelCase__      =			point - 1
																												else:
																																			lowerCAmelCase__      =			point + 1
							return None


def       _snake_case     (  A				,					A				,					A				,					A )		->					Any:

							# avoid divided by 0 during interpolation
							if sorted_collection[left] == sorted_collection[right]:
														if sorted_collection[left] == item:
																					return left
														else:
																					return None

							lowerCAmelCase__      =			left + ((item - sorted_collection[left]) * (right - left)) // (
							    sorted_collection[right] - sorted_collection[left]
							)

							# out of range check
							if point < 0 or point >= len(A ):
														return None

							if sorted_collection[point] == item:
														return point
							elif point < left:
														return interpolation_search_by_recursion(A				,					A				,					A				,					A )
							elif point > right:
														return interpolation_search_by_recursion(A				,					A				,					A				,					A )
							else:
														if sorted_collection[point] > item:
																					return interpolation_search_by_recursion(
																					    A				,					A				,					A				,					point - 1 )
														else:
																					return interpolation_search_by_recursion(
																					    A				,					A				,					point + 1				,					A )


def       _snake_case     (  A )		->					Dict:
							if collection != sorted(A ):
														raise ValueError('''Collection must be ascending sorted''' )
							return True


if __name__ == "__main__":
		import sys
		__UpperCAmelCase					       =							0
		if debug == 1:
				__UpperCAmelCase					       =							[10, 30, 40, 45, 50, 66, 77, 93]
				try:
						__assert_sorted(collection)
				except ValueError:
						sys.exit('''Sequence must be ascending sorted to apply interpolation search''')
				__UpperCAmelCase					       =							67

		__UpperCAmelCase					       =							interpolation_search(collection, target)
		if result is not None:
				print(f"""{target} found at positions: {result}""")
		else:
				print('''Not found''')



'''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