





import math






def lowerCamelCase__   (							snake_case_     :  list	,				snake_case_     :  int = 0	,				snake_case_     :  int = 0	)				->    list:
			__snake_case								=       end or len(UpperCAmelCase_	)
			for i in range(UpperCAmelCase_	,				UpperCAmelCase_	):
						__snake_case								=       i
						__snake_case								=       array[i]
						while temp_index != start and temp_index_value < array[temp_index - 1]:
									__snake_case								=       array[temp_index - 1]
									temp_index -= 1
						__snake_case								=       temp_index_value
			return array






def lowerCamelCase__   (							snake_case_     :  list	,				snake_case_     :  int	,				snake_case_     :  int	)				->    None:  # Max Heap
			__snake_case								=       index
			__snake_case								=       2 * index + 1  # Left Node
			__snake_case								=       2 * index + 2  # Right Node

			if left_index < heap_size and array[largest] < array[left_index]:
						__snake_case								=       left_index

			if right_index < heap_size and array[largest] < array[right_index]:
						__snake_case								=       right_index

			if largest != index:
						__snake_case								=       array[largest], array[index]
						heapify(UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	)






def lowerCamelCase__   (							snake_case_     :  list	)				->    list:
			__snake_case								=       len(UpperCAmelCase_	)

			for i in range(n // 2	,				-1	,				-1	):
						heapify(UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	)

			for i in range(n - 1	,				0	,				-1	):
						__snake_case								=       array[0], array[i]
						heapify(UpperCAmelCase_	,				0	,				UpperCAmelCase_	)

			return array






def lowerCamelCase__   (							snake_case_     :  list	,				snake_case_     :  int	,				snake_case_     :  int	,				snake_case_     :  int	)				->    int:





			if (array[first_index] > array[middle_index]) != (
			    array[first_index] > array[last_index]
			):
						return array[first_index]
			elif (array[middle_index] > array[first_index]) != (
			    array[middle_index] > array[last_index]
			):
						return array[middle_index]
			else:
						return array[last_index]






def lowerCamelCase__   (							snake_case_     :  list	,				snake_case_     :  int	,				snake_case_     :  int	,				snake_case_     :  int	)				->    int:
			__snake_case								=       low
			__snake_case								=       high
			while True:
						while array[i] < pivot:
									i += 1
						j -= 1
						while pivot < array[j]:
									j -= 1
						if i >= j:
									return i
						__snake_case								=       array[j], array[i]
						i += 1






def lowerCamelCase__   (							snake_case_     :  list	)				->    list:





			if len(UpperCAmelCase_	) == 0:
						return array
			__snake_case								=       2 * math.ceil(math.loga(len(UpperCAmelCase_	)	)	)
			__snake_case								=       16
			return intro_sort(UpperCAmelCase_	,				0	,				len(UpperCAmelCase_	)	,				UpperCAmelCase_	,				UpperCAmelCase_	)






def lowerCamelCase__   (							snake_case_     :  list	,				snake_case_     :  int	,				snake_case_     :  int	,				snake_case_     :  int	,				snake_case_     :  int	)				->    list:





			while end - start > size_threshold:
						if max_depth == 0:
									return heap_sort(UpperCAmelCase_	)
						max_depth -= 1
						__snake_case								=       median_of_a(UpperCAmelCase_	,				UpperCAmelCase_	,				start + ((end - start) // 2) + 1	,				end - 1	)
						__snake_case								=       partition(UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	)
						intro_sort(UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	)
						__snake_case								=       p
			return insertion_sort(UpperCAmelCase_	,				UpperCAmelCase_	,				UpperCAmelCase_	)


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				snake_case_           =      input('Enter numbers separated by a comma : ').strip()
				snake_case_           =      [float(item) for item in user_input.split(',')]
				print(sort(unsorted))








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 		SCREAMING_SNAKE_CASE__    (	unittest.TestCase  ):


      def        a			(self	:				int				):





         """simple docstring"""



         super().tearDown()
         gc.collect()


      def        a			(self	:				Dict				):





         """simple docstring"""



         __snake_case	,     __snake_case								=       FlaxControlNetModel.from_pretrained(
             '''lllyasviel/sd-controlnet-canny'''    ,      from_pt=a__    ,      dtype=jnp.bfloataa				)
         __snake_case	,     __snake_case								=       FlaxStableDiffusionControlNetPipeline.from_pretrained(
             '''runwayml/stable-diffusion-v1-5'''    ,      controlnet=a__    ,      from_pt=a__    ,      dtype=jnp.bfloataa				)
         __snake_case								=       controlnet_params

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

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

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

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

         __snake_case								=       pipe(
             prompt_ids=a__    ,      image=a__    ,      params=a__    ,      prng_seed=a__    ,      num_inference_steps=50    ,      jit=a__    ,      ).images
         assert images.shape == (jax.device_count(), 1, 768, 512, 3)

         __snake_case								=       images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]				)
         __snake_case								=       images[0, 253:256, 253:256, -1]

         __snake_case								=       jnp.asarray(jax.device_get(image_slice.flatten()				)				)
         __snake_case								=       jnp.array(
             [0.1_6_7_9_6_9, 0.1_1_6_6_9_9, 0.0_8_1_5_4_3, 0.1_5_4_2_9_7, 0.1_3_2_8_1_2, 0.1_0_8_8_8_7, 0.1_6_9_9_2_2, 0.1_6_9_9_2_2, 0.2_0_5_0_7_8]				)
         print(f"""output_slice: {output_slice}"""				)
         assert jnp.abs(output_slice - expected_slice				).max() < 1E-2


      def        a			(self	:				Dict				):





         """simple docstring"""



         __snake_case	,     __snake_case								=       FlaxControlNetModel.from_pretrained(
             '''lllyasviel/sd-controlnet-openpose'''    ,      from_pt=a__    ,      dtype=jnp.bfloataa				)
         __snake_case	,     __snake_case								=       FlaxStableDiffusionControlNetPipeline.from_pretrained(
             '''runwayml/stable-diffusion-v1-5'''    ,      controlnet=a__    ,      from_pt=a__    ,      dtype=jnp.bfloataa				)
         __snake_case								=       controlnet_params

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

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

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

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

         __snake_case								=       pipe(
             prompt_ids=a__    ,      image=a__    ,      params=a__    ,      prng_seed=a__    ,      num_inference_steps=50    ,      jit=a__    ,      ).images
         assert images.shape == (jax.device_count(), 1, 768, 512, 3)

         __snake_case								=       images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]				)
         __snake_case								=       images[0, 253:256, 253:256, -1]

         __snake_case								=       jnp.asarray(jax.device_get(image_slice.flatten()				)				)
         __snake_case								=       jnp.array(
             [[0.2_7_1_4_8_4, 0.2_6_1_7_1_9, 0.2_7_5_3_9_1, 0.2_7_7_3_4_4, 0.2_7_9_2_9_7, 0.2_9_1_0_1_6, 0.2_9_4_9_2_2, 0.3_0_2_7_3_4, 0.3_0_2_7_3_4]]				)
         print(f"""output_slice: {output_slice}"""				)
         assert jnp.abs(output_slice - expected_slice				).max() < 1E-2

