



from __future__ import annotations

import math





class  __magic_name__   :






		def __init__(						self      :     Optional[int]				,		UpperCamelCase__      :     int      )				->					None:
								'''simple docstring'''







								UpperCAmelCase         =     size
								# approximate the overall size of segment tree with given value
								UpperCAmelCase         =     [0 for i in range(0				,		4 * size      )]
								# create array to store lazy update
								UpperCAmelCase         =     [0 for i in range(0				,		4 * size      )]
								UpperCAmelCase         =     [0 for i in range(0				,		4 * size      )]  # flag for lazy update






		def SCREAMING_SNAKE_CASE_			(						self      :     str				,		UpperCamelCase__      :     int      )				->					int:
								'''simple docstring'''







								return idx * 2






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple				,		UpperCamelCase__      :     int      )				->					int:
								'''simple docstring'''







								return idx * 2 + 1






		def SCREAMING_SNAKE_CASE_			(						self      :     str				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     list[int]      )				->					None:
								'''simple docstring'''







								if left_element == right_element:
														UpperCAmelCase         =     a[left_element - 1]
								else:
														UpperCAmelCase         =     (left_element + right_element) // 2
														self.build(self.left(UpperCamelCase__      )				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__      )
														self.build(self.right(UpperCamelCase__      )				,		mid + 1				,		UpperCamelCase__				,		UpperCamelCase__      )
														UpperCAmelCase         =     max(
														    self.segment_tree[self.left(UpperCamelCase__      )]				,		self.segment_tree[self.right(UpperCamelCase__      )]      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Dict				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int      )				->					bool:
								'''simple docstring'''







								if self.flag[idx] is True:
														UpperCAmelCase         =     self.lazy[idx]
														UpperCAmelCase         =     False
														if left_element != right_element:
																				UpperCAmelCase         =     self.lazy[idx]
																				UpperCAmelCase         =     self.lazy[idx]
																				UpperCAmelCase         =     True
																				UpperCAmelCase         =     True

								if right_element < a or left_element > b:
														return True
								if left_element >= a and right_element <= b:
														UpperCAmelCase         =     val
														if left_element != right_element:
																				UpperCAmelCase         =     val
																				UpperCAmelCase         =     val
																				UpperCAmelCase         =     True
																				UpperCAmelCase         =     True
														return True
								UpperCAmelCase         =     (left_element + right_element) // 2
								self.update(self.left(UpperCamelCase__      )				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__      )
								self.update(self.right(UpperCamelCase__      )				,		mid + 1				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__      )
								UpperCAmelCase         =     max(
								    self.segment_tree[self.left(UpperCamelCase__      )]				,		self.segment_tree[self.right(UpperCamelCase__      )]      )
								return True






		def SCREAMING_SNAKE_CASE_			(						self      :     Dict				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int				,		UpperCamelCase__      :     int      )				->					int | float:
								'''simple docstring'''







								if self.flag[idx] is True:
														UpperCAmelCase         =     self.lazy[idx]
														UpperCAmelCase         =     False
														if left_element != right_element:
																				UpperCAmelCase         =     self.lazy[idx]
																				UpperCAmelCase         =     self.lazy[idx]
																				UpperCAmelCase         =     True
																				UpperCAmelCase         =     True
								if right_element < a or left_element > b:
														return -math.inf
								if left_element >= a and right_element <= b:
														return self.segment_tree[idx]
								UpperCAmelCase         =     (left_element + right_element) // 2
								UpperCAmelCase         =     self.query(self.left(UpperCamelCase__      )				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__      )
								UpperCAmelCase         =     self.query(self.right(UpperCamelCase__      )				,		mid + 1				,		UpperCamelCase__				,		UpperCamelCase__				,		UpperCamelCase__      )
								return max(UpperCamelCase__				,		UpperCamelCase__      )







		def __str__(						self      :     int      )				->					str:
								'''simple docstring'''







								return str([self.query(1				,		1				,		self.size				,		UpperCamelCase__				,		UpperCamelCase__      ) for i in range(1				,		self.size + 1      )]      )


if __name__ == "__main__":
		__lowerCamelCase     :							int  							=				[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
		__lowerCamelCase     :							List[Any]  							=				15
		__lowerCamelCase     :							List[Any]  							=				SegmentTree(size)
		segt.build(1, 1, size, A)
		print(segt.query(1, 1, size, 4, 6))
		print(segt.query(1, 1, size, 7, 11))
		print(segt.query(1, 1, size, 7, 12))
		segt.update(1, 1, size, 1, 3, 111)
		print(segt.query(1, 1, size, 1, 15))
		segt.update(1, 1, size, 7, 8, 235)
		print(segt)








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  __magic_name__   (							unittest.TestCase						):






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[int]      )				->					Optional[Any]:
								'''simple docstring'''







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






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple      )				->					Dict:
								'''simple docstring'''







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

								UpperCAmelCase         =     "bird"
								UpperCAmelCase         =     jax.device_count()
								UpperCAmelCase         =     pipe.prepare_text_inputs([prompts] * num_samples      )

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

								UpperCAmelCase         =     jax.random.PRNGKey(0      )
								UpperCAmelCase         =     jax.random.split(UpperCamelCase__				,		jax.device_count()      )

								UpperCAmelCase         =     replicate(UpperCamelCase__      )
								UpperCAmelCase         =     shard(UpperCamelCase__      )
								UpperCAmelCase         =     shard(UpperCamelCase__      )

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

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

								UpperCAmelCase         =     jnp.asarray(jax.device_get(image_slice.flatten()      )      )
								UpperCAmelCase         =     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 SCREAMING_SNAKE_CASE_			(						self      :     Tuple      )				->					Tuple:
								'''simple docstring'''







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

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

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

								UpperCAmelCase         =     jax.random.PRNGKey(0      )
								UpperCAmelCase         =     jax.random.split(UpperCamelCase__				,		jax.device_count()      )

								UpperCAmelCase         =     replicate(UpperCamelCase__      )
								UpperCAmelCase         =     shard(UpperCamelCase__      )
								UpperCAmelCase         =     shard(UpperCamelCase__      )

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

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

								UpperCAmelCase         =     jnp.asarray(jax.device_get(image_slice.flatten()      )      )
								UpperCAmelCase         =     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



