
def 		_UpperCAmelCase   (	UpperCamelCase:     int			,							UpperCamelCase:     Optional[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							0
	__lowerCAmelCase         =							len(UpperCamelCase  ) - 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(UpperCamelCase  ):
			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 		_UpperCAmelCase   (	UpperCamelCase:     Tuple			,							UpperCamelCase:     int			,							UpperCamelCase:     Optional[Any]			,							UpperCamelCase:     Dict  ):






	"""simple docstring"""


	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(UpperCamelCase  ):
		return None

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






def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[Any]  ):






	"""simple docstring"""


	if collection != sorted(UpperCamelCase  ):
		raise ValueError("Collection must be ascending sorted"  )
	return True


if __name__ == "__main__":
					import sys
					UpperCamelCase_   	=	0
					if debug == 1:
										UpperCamelCase_   	=	[1_0, 3_0, 4_0, 4_5, 5_0, 6_6, 7_7, 9_3]
										try:
															__assert_sorted(collection)
										except ValueError:
															sys.exit("Sequence must be ascending sorted to apply interpolation search")
										UpperCamelCase_   	=	6_7

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








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					):
							pass

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







							def       UpperCAmelCase__					(						self  :  Dict ):
								"""simple docstring"""







								__lowerCAmelCase         =							VersatileDiffusionImageVariationPipeline.from_pretrained("shi-labs/versatile-diffusion" )
								pipe.to(snake_case__ )
								pipe.set_progress_bar_config(disable=snake_case__ )

								__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=snake_case__      ,				generator=snake_case__      ,				guidance_scale=7.5      ,				num_inference_steps=50      ,				output_type="numpy"      ,				).images

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

								assert image.shape == (1, 512, 512, 3)
								__lowerCAmelCase         =							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






