


class        a					:





					def __init__(    self					:				List[Any]							):
								__lowerCamelCase:				dict[str, TrieNode]     =	{}  # Mapping from char to TrieNode
								__lowerCamelCase:				str     =	False





					def  SCREAMING_SNAKE_CASE__       (    self					:				List[Any]    ,	SCREAMING_SNAKE_CASE_					:				list[str]							):
								for word in words:
											self.insert(SCREAMING_SNAKE_CASE_							)





					def  SCREAMING_SNAKE_CASE__       (    self					:				int    ,	SCREAMING_SNAKE_CASE_					:				str							):
								__lowerCamelCase:				int     =	self
								for char in word:
											if char not in curr.nodes:
														__lowerCamelCase:				Dict     =	TrieNode()
											__lowerCamelCase:				int     =	curr.nodes[char]
								__lowerCamelCase:				Any     =	True





					def  SCREAMING_SNAKE_CASE__       (    self					:				Optional[Any]    ,	SCREAMING_SNAKE_CASE_					:				str							):
								__lowerCamelCase:				Union[str, Any]     =	self
								for char in word:
											if char not in curr.nodes:
														return False
											__lowerCamelCase:				Tuple     =	curr.nodes[char]
								return curr.is_leaf







					def  SCREAMING_SNAKE_CASE__       (    self					:				List[str]    ,	SCREAMING_SNAKE_CASE_					:				str							):

								def _delete(SCREAMING_SNAKE_CASE_					:				TrieNode    ,	SCREAMING_SNAKE_CASE_					:				str    ,	SCREAMING_SNAKE_CASE_					:				int							) -> bool:
											if index == len(SCREAMING_SNAKE_CASE_							):
														# If word does not exist
														if not curr.is_leaf:
																	return False
														__lowerCamelCase:				Tuple     =	False
														return len(curr.nodes							) == 0
											__lowerCamelCase:				Any     =	word[index]
											__lowerCamelCase:				List[str]     =	curr.nodes.get(SCREAMING_SNAKE_CASE_							)
											# If char not in current trie node
											if not char_node:
														return False
											# Flag to check if node can be deleted
											__lowerCamelCase:				List[str]     =	_delete(SCREAMING_SNAKE_CASE_    ,	SCREAMING_SNAKE_CASE_    ,	index + 1							)
											if delete_curr:
														del curr.nodes[char]
														return len(curr.nodes							) == 0
											return delete_curr

								_delete(self    ,	SCREAMING_SNAKE_CASE_    ,	0							)



def     __lowerCAmelCase						(							snake_case	:    TrieNode						,      snake_case	:    str )       ->							None:
			if node.is_leaf:
						print(snake_case						,      end=""" """ )

			for key, value in node.nodes.items():
						print_words(snake_case						,      word + key )



def     __lowerCAmelCase						(							)       ->							bool:
			__lowerCamelCase:				Tuple     =	"""banana bananas bandana band apple all beast""".split()
			__lowerCamelCase:				Dict     =	TrieNode()
			root.insert_many(snake_case )
			# print_words(root, "")
			assert all(root.find(snake_case ) for word in words )
			assert root.find("""banana""" )
			assert not root.find("""bandanas""" )
			assert not root.find("""apps""" )
			assert root.find("""apple""" )
			assert root.find("""all""" )
			root.delete("""all""" )
			assert not root.find("""all""" )
			root.delete("""banana""" )
			assert not root.find("""banana""" )
			assert root.find("""bananas""" )
			return True



def     __lowerCAmelCase						(							snake_case	:    str						,      snake_case	:    bool )       ->							None:
			print(str(snake_case )						,      """works!""" if passes else """doesn't work :(""" )



def     __lowerCAmelCase						(							)       ->							None:
			assert test_trie()



def     __lowerCAmelCase						(							)       ->							None:
			print_results("""Testing trie functionality"""						,      test_trie() )


if __name__ == "__main__":
			main()






import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
   _A		:				str									=       argparse.ArgumentParser()

   parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

   parser.add_argument(
       '''--txt2img_unclip''',
       default='''kakaobrain/karlo-v1-alpha''',
       type=str,
       required=False,
       help='''The pretrained txt2img unclip.''',
   )

   _A		:				Optional[Any]									=       parser.parse_args()

   _A		:				str									=       UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

   _A		:				Optional[Any]									=       CLIPImageProcessor()
   _A		:				List[Any]									=       CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

   _A		:				str									=       UnCLIPImageVariationPipeline(
       decoder=txtaimg.decoder,
       text_encoder=txtaimg.text_encoder,
       tokenizer=txtaimg.tokenizer,
       text_proj=txtaimg.text_proj,
       feature_extractor=feature_extractor,
       image_encoder=image_encoder,
       super_res_first=txtaimg.super_res_first,
       super_res_last=txtaimg.super_res_last,
       decoder_scheduler=txtaimg.decoder_scheduler,
       super_res_scheduler=txtaimg.super_res_scheduler,
   )

   imgaimg.save_pretrained(args.dump_path)


