


def 							__lowercase       (			__lowerCAmelCase							:    Tuple ,   __lowerCAmelCase							:    Union[str, Any]       ):
							a__					=					0
							a__					=					len(__lowerCAmelCase       ) - 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

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

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

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






def 							__lowercase       (			__lowerCAmelCase							:    Dict ,   __lowerCAmelCase							:    Any ,   __lowerCAmelCase							:    Tuple ,   __lowerCAmelCase							:    Optional[Any]       ):

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

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

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

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






def 							__lowercase       (			__lowerCAmelCase							:    Optional[int]       ):
							if collection != sorted(__lowerCAmelCase       ):
														raise ValueError('Collection must be ascending sorted'       )
							return True


if __name__ == "__main__":
						import sys
						snake_case							:	str					      =				0
						if debug == 1:
												snake_case							:	Union[str, Any]					      =				[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''')
												snake_case							:	Union[str, Any]					      =				67

						snake_case							:	Union[str, Any]					      =				interpolation_search(collection, target)
						if result is not None:
												print(f"""{target} found at positions: {result}""")
						else:
												print('''Not found''')








import gc
import unittest

from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
						import jax
						import jax.numpy as jnp
						from flax.jax_utils import replicate
						from flax.training.common_utils import shard







@slow
@require_flax
class 	snake_case_       (unittest.TestCase				):
					def 			lowerCamelCase__(				self       :List[Any]				) ->   str:
												# clean up the VRAM after each test
												super().tearDown()
												gc.collect()
					def 			lowerCamelCase__(				self       :int				) ->   Optional[Any]:
												a__				, a__					=					FlaxControlNetModel.from_pretrained(
												    'lllyasviel/sd-controlnet-canny'      ,from_pt=__snake_case      ,dtype=jnp.bfloataa				)
												a__				, a__					=					FlaxStableDiffusionControlNetPipeline.from_pretrained(
												    'runwayml/stable-diffusion-v1-5'      ,controlnet=__snake_case      ,from_pt=__snake_case      ,dtype=jnp.bfloataa				)
												a__					=					controlnet_params

												a__					=					'bird'
												a__					=					jax.device_count()
												a__					=					pipe.prepare_text_inputs([prompts] * num_samples				)

												a__					=					load_image(
												    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/bird_canny.png'				)
												a__					=					pipe.prepare_image_inputs([canny_image] * num_samples				)

												a__					=					jax.random.PRNGKey(0				)
												a__					=					jax.random.split(__snake_case      ,jax.device_count()				)

												a__					=					replicate(__snake_case				)
												a__					=					shard(__snake_case				)
												a__					=					shard(__snake_case				)

												a__					=					pipe(
												    prompt_ids=__snake_case      ,image=__snake_case      ,params=__snake_case      ,prng_seed=__snake_case      ,num_inference_steps=50      ,jit=__snake_case      ,).images
												assert images.shape == (jax.device_count(), 1, 7_68, 5_12, 3)

												a__					=					images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]				)
												a__					=					images[0, 2_53:2_56, 2_53:2_56, -1]

												a__					=					jnp.asarray(jax.device_get(image_slice.flatten()				)				)
												a__					=					jnp.array(
												    [0.16_79_69, 0.11_66_99, 0.08_15_43, 0.15_42_97, 0.13_28_12, 0.10_88_87, 0.16_99_22, 0.16_99_22, 0.20_50_78]				)
												print(F'output_slice: {output_slice}'				)
												assert jnp.abs(output_slice - expected_slice				).max() < 1E-2



					def 			lowerCamelCase__(				self       :Optional[Any]				) ->   Optional[Any]:
												a__				, a__					=					FlaxControlNetModel.from_pretrained(
												    'lllyasviel/sd-controlnet-openpose'      ,from_pt=__snake_case      ,dtype=jnp.bfloataa				)
												a__				, a__					=					FlaxStableDiffusionControlNetPipeline.from_pretrained(
												    'runwayml/stable-diffusion-v1-5'      ,controlnet=__snake_case      ,from_pt=__snake_case      ,dtype=jnp.bfloataa				)
												a__					=					controlnet_params

												a__					=					'Chef in the kitchen'
												a__					=					jax.device_count()
												a__					=					pipe.prepare_text_inputs([prompts] * num_samples				)

												a__					=					load_image(
												    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/sd_controlnet/pose.png'				)
												a__					=					pipe.prepare_image_inputs([pose_image] * num_samples				)

												a__					=					jax.random.PRNGKey(0				)
												a__					=					jax.random.split(__snake_case      ,jax.device_count()				)

												a__					=					replicate(__snake_case				)
												a__					=					shard(__snake_case				)
												a__					=					shard(__snake_case				)

												a__					=					pipe(
												    prompt_ids=__snake_case      ,image=__snake_case      ,params=__snake_case      ,prng_seed=__snake_case      ,num_inference_steps=50      ,jit=__snake_case      ,).images
												assert images.shape == (jax.device_count(), 1, 7_68, 5_12, 3)

												a__					=					images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]				)
												a__					=					images[0, 2_53:2_56, 2_53:2_56, -1]

												a__					=					jnp.asarray(jax.device_get(image_slice.flatten()				)				)
												a__					=					jnp.array(
												    [[0.27_14_84, 0.26_17_19, 0.27_53_91, 0.27_73_44, 0.27_92_97, 0.29_10_16, 0.29_49_22, 0.30_27_34, 0.30_27_34]]				)
												print(F'output_slice: {output_slice}'				)
												assert jnp.abs(output_slice - expected_slice				).max() < 1E-2




