class  _a							:




	def __init__( self						:		Optional[Any]		, _SCREAMING_SNAKE_CASE						:		Any = ""		, _SCREAMING_SNAKE_CASE						:		str = False		)->	Any:
			# Mapping from the first character of the prefix of the node
			lowerCAmelCase__       :      Any   					= {}

			# A node will be a leaf if the tree contains its word
			lowerCAmelCase__       :      Dict   					= is_leaf

			lowerCAmelCase__       :      str   					= prefix




	def 							UpperCAmelCase__( self						:		List[str]		, _SCREAMING_SNAKE_CASE						:		List[Any]		)->	int:
			lowerCAmelCase__       :      Tuple   					= 0
			for q, w in zip(self.prefix		, __lowerCamelCase		):
					if q != w:
							break

					x += 1

			return self.prefix[:x], self.prefix[x:], word[x:]




	def 							UpperCAmelCase__( self						:		List[str]		, _SCREAMING_SNAKE_CASE						:		List[Any]		)->	Any:
			for word in words:
					self.insert(__lowerCamelCase		)




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		List[Any]		)->	Dict:
			# Case 1: If the word is the prefix of the node
			# Solution: We set the current node as leaf
			if self.prefix == word:
					lowerCAmelCase__       :      int   					= True

			# Case 2: The node has no edges that have a prefix to the word
			# Solution: We create an edge from the current node to a new one
			# containing the word
			elif word[0] not in self.nodes:
					lowerCAmelCase__       :      Dict   					= RadixNode(prefix=__lowerCamelCase		, is_leaf=__lowerCamelCase		)

			else:
					lowerCAmelCase__       :      Union[str, Any]   					= self.nodes[word[0]]
					lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__       :      Tuple   					= incoming_node.match(
					    __lowerCamelCase		)

					# Case 3: The node prefix is equal to the matching
					# Solution: We insert remaining word on the next node
					if remaining_prefix == "":
							self.nodes[matching_string[0]].insert(__lowerCamelCase		)

					# Case 4: The word is greater equal to the matching
					# Solution: Create a node in between both nodes, change
					# prefixes and add the new node for the remaining word
					else:
							lowerCAmelCase__       :      Tuple   					= remaining_prefix

							lowerCAmelCase__       :      List[str]   					= self.nodes[matching_string[0]]
							lowerCAmelCase__       :      Any   					= RadixNode(__lowerCamelCase		, __lowerCamelCase		)
							lowerCAmelCase__       :      int   					= aux_node

							if remaining_word == "":
									lowerCAmelCase__       :      int   					= True
							else:
									self.nodes[matching_string[0]].insert(__lowerCamelCase		)




	def 							UpperCAmelCase__( self						:		str		, _SCREAMING_SNAKE_CASE						:		Dict		)->	Dict:
			lowerCAmelCase__       :      List[str]   					= self.nodes.get(word[0]		, __lowerCamelCase		)
			if not incoming_node:
					return False
			else:
					lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__       :      Union[str, Any]   					= incoming_node.match(
					    __lowerCamelCase		)
					# If there is remaining prefix, the word can't be on the tree
					if remaining_prefix != "":
							return False
					# This applies when the word and the prefix are equal
					elif remaining_word == "":
							return incoming_node.is_leaf
					# We have word remaining so we check the next node
					else:
							return incoming_node.find(__lowerCamelCase		)




	def 							UpperCAmelCase__( self						:		Any		, _SCREAMING_SNAKE_CASE						:		Any		)->	Optional[Any]:
			lowerCAmelCase__       :      Union[str, Any]   					= self.nodes.get(word[0]		, __lowerCamelCase		)
			if not incoming_node:
					return False
			else:
					lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__       :      str   					= incoming_node.match(
					    __lowerCamelCase		)
					# If there is remaining prefix, the word can't be on the tree
					if remaining_prefix != "":
							return False
					# We have word remaining so we check the next node
					elif remaining_word != "":
							return incoming_node.delete(__lowerCamelCase		)
					else:
							# If it is not a leaf, we don't have to delete
							if not incoming_node.is_leaf:
									return False
							else:
									# We delete the nodes if no edges go from it
									if len(incoming_node.nodes		) == 0:
											del self.nodes[word[0]]
											# We merge the current node with its only child
											if len(self.nodes		) == 1 and not self.is_leaf:
													lowerCAmelCase__       :      Optional[Any]   					= list(self.nodes.values()		)[0]
													lowerCAmelCase__       :      int   					= merging_node.is_leaf
													self.prefix += merging_node.prefix
													lowerCAmelCase__       :      int   					= merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
									elif len(incoming_node.nodes		) > 1:
											lowerCAmelCase__       :      Optional[Any]   					= False
									# If there is 1 edge, we merge it with its child
									else:
											lowerCAmelCase__       :      Any   					= list(incoming_node.nodes.values()		)[0]
											lowerCAmelCase__       :      Tuple   					= merging_node.is_leaf
											incoming_node.prefix += merging_node.prefix
											lowerCAmelCase__       :      Dict   					= merging_node.nodes

									return True




	def 							UpperCAmelCase__( self						:		Optional[Any]		, _SCREAMING_SNAKE_CASE						:		Optional[int] = 0		)->	List[Any]:
			if self.prefix != "":
					print('''-''' * height		, self.prefix		, '''  (leaf)''' if self.is_leaf else ''''''		)

			for value in self.nodes.values():
					value.print_tree(height + 1		)






def 					lowerCamelCase_   (	):




		"""simple docstring"""






		lowerCAmelCase__       :      Union[str, Any]   					= '''banana bananas bandana band apple all beast'''.split()
		lowerCAmelCase__       :      str   					= RadixNode()
		root.insert_many(UpperCamelCase__	)

		assert all(root.find(UpperCamelCase__	) for word in words	)
		assert not root.find('''bandanas'''	)
		assert not root.find('''apps'''	)
		root.delete('''all'''	)
		assert not root.find('''all'''	)
		root.delete('''banana'''	)
		assert not root.find('''banana'''	)
		assert root.find('''bananas'''	)

		return True






def 					lowerCamelCase_   (	):




		"""simple docstring"""






		assert test_trie()






def 					lowerCamelCase_   (	):




		"""simple docstring"""






		lowerCAmelCase__       :      List[Any]   					= RadixNode()
		lowerCAmelCase__       :      Optional[Any]   					= '''banana bananas bandanas bandana band apple all beast'''.split()
		root.insert_many(UpperCamelCase__	)

		print('''Words:'''     ,       UpperCamelCase__	)
		print('''Tree:'''	)
		root.print_tree()


if __name__ == "__main__":
		main()








import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


lowerCamelCase						=		False





class  _a							(    unittest.TestCase):
	pass





@nightly
@require_torch_gpu
class  _a							(    unittest.TestCase):




	def 							UpperCAmelCase__( self						:		int		)->	int:
			# clean up the VRAM after each test
			super().tearDown()
			gc.collect()
			torch.cuda.empty_cache()




	def 							UpperCAmelCase__( self						:		Any		)->	Dict:
			lowerCAmelCase__       :      int   					= VersatileDiffusionPipeline.from_pretrained('''shi-labs/versatile-diffusion'''		, torch_dtype=torch.floataa		)
			pipe.to(_SCREAMING_SNAKE_CASE		)
			pipe.set_progress_bar_config(disable=_SCREAMING_SNAKE_CASE		)

			lowerCAmelCase__       :      List[str]   					= load_image(
			    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''		)

			lowerCAmelCase__       :      List[str]   					= torch.manual_seed(0		)
			lowerCAmelCase__       :      List[str]   					= pipe.dual_guided(
			    prompt='''first prompt'''		, image=_SCREAMING_SNAKE_CASE		, text_to_image_strength=0.75		, generator=_SCREAMING_SNAKE_CASE		, guidance_scale=7.5		, num_inference_steps=2		, output_type='''numpy'''		, ).images

			with tempfile.TemporaryDirectory() as tmpdirname:
					pipe.save_pretrained(_SCREAMING_SNAKE_CASE		)
					lowerCAmelCase__       :      List[Any]   					= VersatileDiffusionPipeline.from_pretrained(_SCREAMING_SNAKE_CASE		, torch_dtype=torch.floataa		)
			pipe.to(_SCREAMING_SNAKE_CASE		)
			pipe.set_progress_bar_config(disable=_SCREAMING_SNAKE_CASE		)

			lowerCAmelCase__       :      List[str]   					= generator.manual_seed(0		)
			lowerCAmelCase__       :      str   					= pipe.dual_guided(
			    prompt='''first prompt'''		, image=_SCREAMING_SNAKE_CASE		, text_to_image_strength=0.75		, generator=_SCREAMING_SNAKE_CASE		, guidance_scale=7.5		, num_inference_steps=2		, output_type='''numpy'''		, ).images

			assert np.abs(image - new_image		).sum() < 1E-5, "Models don't have the same forward pass"




	def 							UpperCAmelCase__( self						:		Tuple		)->	List[Any]:
			lowerCAmelCase__       :      Optional[int]   					= VersatileDiffusionPipeline.from_pretrained('''shi-labs/versatile-diffusion'''		, torch_dtype=torch.floataa		)
			pipe.to(_SCREAMING_SNAKE_CASE		)
			pipe.set_progress_bar_config(disable=_SCREAMING_SNAKE_CASE		)

			lowerCAmelCase__       :      int   					= '''cyberpunk 2077'''
			lowerCAmelCase__       :      List[str]   					= load_image(
			    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''		)
			lowerCAmelCase__       :      List[Any]   					= torch.manual_seed(0		)
			lowerCAmelCase__       :      Union[str, Any]   					= pipe.dual_guided(
			    prompt=_SCREAMING_SNAKE_CASE		, image=_SCREAMING_SNAKE_CASE		, text_to_image_strength=0.75		, generator=_SCREAMING_SNAKE_CASE		, guidance_scale=7.5		, num_inference_steps=50		, output_type='''numpy'''		, ).images

			lowerCAmelCase__       :      List[Any]   					= image[0, 253:256, 253:256, -1]

			assert image.shape == (1, 512, 512, 3)
			lowerCAmelCase__       :      List[str]   					= np.array([0.1448, 0.1619, 0.1741, 0.1086, 0.1147, 0.1128, 0.1199, 0.1165, 0.1001]		)

			assert np.abs(image_slice.flatten() - expected_slice		).max() < 1E-1

			lowerCAmelCase__       :      int   					= '''A painting of a squirrel eating a burger '''
			lowerCAmelCase__       :      Optional[Any]   					= torch.manual_seed(0		)
			lowerCAmelCase__       :      Union[str, Any]   					= pipe.text_to_image(
			    prompt=_SCREAMING_SNAKE_CASE		, generator=_SCREAMING_SNAKE_CASE		, guidance_scale=7.5		, num_inference_steps=50		, output_type='''numpy'''		).images

			lowerCAmelCase__       :      List[Any]   					= image[0, 253:256, 253:256, -1]

			assert image.shape == (1, 512, 512, 3)
			lowerCAmelCase__       :      Optional[Any]   					= np.array([0.3367, 0.3169, 0.2656, 0.3870, 0.4790, 0.3796, 0.4009, 0.4878, 0.4778]		)

			assert np.abs(image_slice.flatten() - expected_slice		).max() < 1E-1

			lowerCAmelCase__       :      Optional[Any]   					= pipe.image_variation(_SCREAMING_SNAKE_CASE		, generator=_SCREAMING_SNAKE_CASE		, output_type='''numpy'''		).images

			lowerCAmelCase__       :      List[Any]   					= image[0, 253:256, 253:256, -1]

			assert image.shape == (1, 512, 512, 3)
			lowerCAmelCase__       :      Any   					= np.array([0.3076, 0.3123, 0.3284, 0.3782, 0.3770, 0.3894, 0.4297, 0.4331, 0.4456]		)

			assert np.abs(image_slice.flatten() - expected_slice		).max() < 1E-1




