





from collections.abc import Iterable
from typing import Any



class    _a     :






							"""simple docstring"""

							def __init__(      self				:     Union[str, Any]							,	a				:     int | None = None    )	->str:
													SCREAMING_SNAKE_CASE__     :				Dict   =					value
													SCREAMING_SNAKE_CASE__     :				Node | None   =					None  # Added in order to delete a node easier
													SCREAMING_SNAKE_CASE__     :				Node | None   =					None
													SCREAMING_SNAKE_CASE__     :				Node | None   =					None






							def __repr__(      self				:     int    )	->str:
													from pprint import pformat

													if self.left is None and self.right is None:
																			return str(self.value    )
													return pformat({f"""{self.value}""": (self.left, self.right)}							,	indent=1    )







class    _a     :






							"""simple docstring"""

							def __init__(      self				:     Optional[int]							,	a				:     Node | None = None    )	->Any:
													SCREAMING_SNAKE_CASE__     :				Dict   =					root

							def __str__(      self				:     str    )	->str:
													return str(self.root    )

							def      A_  (      self				:     str							,	a				:     Node							,	a				:     Node | None    )	->None:
													if new_children is not None:  # reset its kids
																			SCREAMING_SNAKE_CASE__     :				List[str]   =					node.parent
													if node.parent is not None:  # reset its parent
																			if self.is_right(a    ):  # If it is the right children
																									SCREAMING_SNAKE_CASE__     :				Dict   =					new_children
																			else:
																									SCREAMING_SNAKE_CASE__     :				Any   =					new_children
													else:
																			SCREAMING_SNAKE_CASE__     :				List[str]   =					new_children

							def      A_  (      self				:     str							,	a				:     Node    )	->bool:
													if node.parent and node.parent.right:
																			return node == node.parent.right
													return False

							def      A_  (      self				:     Union[str, Any]    )	->bool:
													return self.root is None

							def      A_  (      self				:     Optional[int]							,	a				:     Dict    )	->None:
													SCREAMING_SNAKE_CASE__     :				List[Any]   =					Node(a    )  # create a new Node
													if self.empty():  # if Tree is empty
																			SCREAMING_SNAKE_CASE__     :				Dict   =					new_node  # set its root
													else:  # Tree is not empty
																			SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					self.root  # from root
																			if parent_node is None:
																									return
																			while True:  # While we don't get to a leaf
																									if value < parent_node.value:  # We go left
																															if parent_node.left is None:
																																					SCREAMING_SNAKE_CASE__     :				List[Any]   =					new_node  # We insert the new node in a leaf
																																					break
																															else:
																																					SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					parent_node.left
																									else:
																															if parent_node.right is None:
																																					SCREAMING_SNAKE_CASE__     :				Optional[int]   =					new_node
																																					break
																															else:
																																					SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					parent_node.right
																			SCREAMING_SNAKE_CASE__     :				List[str]   =					parent_node

							def      A_  (      self				:     Union[str, Any]							,	*a				:     int    )	->None:
													for value in values:
																			self.__insert(a    )

							def      A_  (      self				:     Any							,	a				:     Any    )	->Node | None:
													if self.empty():
																			raise IndexError("Warning: Tree is empty! please use another."    )
													else:
																			SCREAMING_SNAKE_CASE__     :				Tuple   =					self.root
																			# use lazy evaluation here to avoid NoneType Attribute error
																			while node is not None and node.value is not value:
																									SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					node.left if value < node.value else node.right
																			return node

							def      A_  (      self				:     Optional[Any]							,	a				:     Node | None = None    )	->Node | None:
													if node is None:
																			if self.root is None:
																									return None
																			SCREAMING_SNAKE_CASE__     :				str   =					self.root

													if not self.empty():
																			while node.right is not None:
																									SCREAMING_SNAKE_CASE__     :				int   =					node.right
													return node

							def      A_  (      self				:     List[Any]							,	a				:     Node | None = None    )	->Node | None:
													if node is None:
																			SCREAMING_SNAKE_CASE__     :				Tuple   =					self.root
													if self.root is None:
																			return None
													if not self.empty():
																			SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					self.root
																			while node.left is not None:
																									SCREAMING_SNAKE_CASE__     :				Tuple   =					node.left
													return node

							def      A_  (      self				:     Optional[Any]							,	a				:     int    )	->None:
													SCREAMING_SNAKE_CASE__     :				Dict   =					self.search(a    )  # Look for the node with that label
													if node is not None:
																			if node.left is None and node.right is None:  # If it has no children
																									self.__reassign_nodes(a							,	a    )
																			elif node.left is None:  # Has only right children
																									self.__reassign_nodes(a							,	node.right    )
																			elif node.right is None:  # Has only left children
																									self.__reassign_nodes(a							,	node.left    )
																			else:
																									SCREAMING_SNAKE_CASE__     :				int   =					self.get_max(
																									    node.left    )  # Gets the max value of the left branch
																									self.remove(tmp_node.value    )  # type: ignore
																									SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					(
																									    tmp_node.value  # type: ignore
																									)  # Assigns the value to the node to delete and keep tree structure

							def      A_  (      self				:     Any							,	a				:     Node | None    )	->Iterable:
													if node is not None:
																			yield node  # Preorder Traversal
																			yield from self.preorder_traverse(node.left    )
																			yield from self.preorder_traverse(node.right    )

							def      A_  (      self				:     str							,	a				:     List[Any]=None    )	->Any:
													if traversal_function is None:
																			return self.preorder_traverse(self.root    )
													else:
																			return traversal_function(self.root    )

							def      A_  (      self				:     List[Any]							,	a				:     list							,	a				:     Node | None    )	->None:
													if node:
																			self.inorder(a							,	node.left    )
																			arr.append(node.value    )
																			self.inorder(a							,	node.right    )






							def      A_  (      self				:     Optional[Any]							,	a				:     int							,	a				:     Node    )	->int:
													SCREAMING_SNAKE_CASE__     :				list[int]   =					[]
													self.inorder(a							,	a    )  # append all values to list using inorder traversal
													return arr[k - 1]







def       UpperCAmelCase							(     _lowerCamelCase      :  Node | None     ):





						'''simple docstring'''


						SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					[]
						if curr_node is not None:
												SCREAMING_SNAKE_CASE__     :				Optional[int]   =					postorder(curr_node.left     ) + postorder(curr_node.right     ) + [curr_node]
						return node_list







def       UpperCAmelCase							(     ):





						'''simple docstring'''


						SCREAMING_SNAKE_CASE__     :				List[str]   =					(8, 3, 6, 1, 10, 14, 13, 4, 7)
						SCREAMING_SNAKE_CASE__     :				List[str]   =					BinarySearchTree()
						for i in testlist:
												t.insert(_lowerCamelCase     )

						# Prints all the elements of the list in order traversal
						print(_lowerCamelCase     )

						if t.search(6     ) is not None:
												print("The value 6 exists"     )
						else:
												print("The value 6 doesn't exist"     )

						if t.search(-1     ) is not None:
												print("The value -1 exists"     )
						else:
												print("The value -1 doesn't exist"     )

						if not t.empty():
												print("Max Value: "			,   t.get_max().value     )  # type: ignore
												print("Min Value: "			,   t.get_min().value     )  # type: ignore

						for i in testlist:
												t.remove(_lowerCamelCase     )
												print(_lowerCamelCase     )


if __name__ == "__main__":
				import doctest

				doctest.testmod(verbose=True)






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    _a     (				unittest.TestCase							):






							"""simple docstring"""

							def      A_  (      self				:     Dict    )	->List[Any]:
													# clean up the VRAM after each test
													super().tearDown()
													gc.collect()

							def      A_  (      self				:     Dict    )	->Tuple:
													SCREAMING_SNAKE_CASE__,							SCREAMING_SNAKE_CASE__     :				Dict   =					FlaxControlNetModel.from_pretrained(
													    "lllyasviel/sd-controlnet-canny"							,	from_pt=a							,	dtype=jnp.bfloataa    )
													SCREAMING_SNAKE_CASE__,							SCREAMING_SNAKE_CASE__     :				Dict   =					FlaxStableDiffusionControlNetPipeline.from_pretrained(
													    "runwayml/stable-diffusion-v1-5"							,	controlnet=a							,	from_pt=a							,	dtype=jnp.bfloataa    )
													SCREAMING_SNAKE_CASE__     :				List[Any]   =					controlnet_params

													SCREAMING_SNAKE_CASE__     :				Dict   =					"bird"
													SCREAMING_SNAKE_CASE__     :				List[Any]   =					jax.device_count()
													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					pipe.prepare_text_inputs([prompts] * num_samples    )

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

													SCREAMING_SNAKE_CASE__     :				List[Any]   =					jax.random.PRNGKey(0    )
													SCREAMING_SNAKE_CASE__     :				int   =					jax.random.split(a							,	jax.device_count()    )

													SCREAMING_SNAKE_CASE__     :				List[Any]   =					replicate(a    )
													SCREAMING_SNAKE_CASE__     :				List[str]   =					shard(a    )
													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					shard(a    )

													SCREAMING_SNAKE_CASE__     :				Dict   =					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, 7_68, 5_12, 3)

													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					images.reshape((images.shape[0] * images.shape[1],) + images.shape[-3:]    )
													SCREAMING_SNAKE_CASE__     :				List[Any]   =					images[0, 2_53:2_56, 2_53:2_56, -1]

													SCREAMING_SNAKE_CASE__     :				Tuple   =					jnp.asarray(jax.device_get(image_slice.flatten()    )    )
													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					jnp.array(
													    [0.16_7969, 0.11_6699, 0.08_1543, 0.15_4297, 0.13_2812, 0.10_8887, 0.16_9922, 0.16_9922, 0.20_5078]    )
													print(f"""output_slice: {output_slice}"""    )
													assert jnp.abs(output_slice - expected_slice    ).max() < 1E-2






							def      A_  (      self				:     List[Any]    )	->Optional[Any]:
													SCREAMING_SNAKE_CASE__,							SCREAMING_SNAKE_CASE__     :				int   =					FlaxControlNetModel.from_pretrained(
													    "lllyasviel/sd-controlnet-openpose"							,	from_pt=a							,	dtype=jnp.bfloataa    )
													SCREAMING_SNAKE_CASE__,							SCREAMING_SNAKE_CASE__     :				Optional[int]   =					FlaxStableDiffusionControlNetPipeline.from_pretrained(
													    "runwayml/stable-diffusion-v1-5"							,	controlnet=a							,	from_pt=a							,	dtype=jnp.bfloataa    )
													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					controlnet_params

													SCREAMING_SNAKE_CASE__     :				Any   =					"Chef in the kitchen"
													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					jax.device_count()
													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					pipe.prepare_text_inputs([prompts] * num_samples    )

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

													SCREAMING_SNAKE_CASE__     :				Any   =					jax.random.PRNGKey(0    )
													SCREAMING_SNAKE_CASE__     :				List[str]   =					jax.random.split(a							,	jax.device_count()    )

													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					replicate(a    )
													SCREAMING_SNAKE_CASE__     :				Tuple   =					shard(a    )
													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					shard(a    )

													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					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, 7_68, 5_12, 3)

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

													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					jnp.asarray(jax.device_get(image_slice.flatten()    )    )
													SCREAMING_SNAKE_CASE__     :				Union[str, Any]   =					jnp.array(
													    [[0.27_1484, 0.26_1719, 0.27_5391, 0.27_7344, 0.27_9297, 0.29_1016, 0.29_4922, 0.30_2734, 0.30_2734]]    )
													print(f"""output_slice: {output_slice}"""    )
													assert jnp.abs(output_slice - expected_slice    ).max() < 1E-2