

'''simple docstring'''


from __future__ import annotations

lowerCAmelCase__										= "#"



class 					lowercase						:


							def __init__(			self)							->				None:
								UpperCAmelCase_		:      dict       	=					{}


							def 						_snake_case							(			self    ,			_snake_case)							->				None:
								UpperCAmelCase_		:      int       	=					self._trie
								for char in text:
									if char not in trie:
										UpperCAmelCase_		:      Dict       	=					{}
									UpperCAmelCase_		:      Optional[Any]       	=					trie[char]
								UpperCAmelCase_		:      Dict       	=					True


							def 						_snake_case							(			self    ,			_snake_case)							->				tuple | list:
								UpperCAmelCase_		:      Any       	=					self._trie
								for char in prefix:
									if char in trie:
										UpperCAmelCase_		:      str       	=					trie[char]
									else:
										return []
								return self._elements(_snake_case)





							def 						_snake_case							(			self    ,			_snake_case)							->				tuple:
								UpperCAmelCase_		:      Any       	=					[]
								for c, v in d.items():
									UpperCAmelCase_		:      Union[str, Any]       	=					[' '] if c == END else [(c + s) for s in self._elements(_snake_case)]
									result.extend(_snake_case)
								return tuple(_snake_case)


lowerCAmelCase__										= Trie()
lowerCAmelCase__										= ("depart", "detergent", "daring", "dog", "deer", "deal")
for word in words:
						trie.insert_word(word)







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase  )    ->    tuple:
	UpperCAmelCase_		:      List[Any]       	=					trie.find_word(UpperCamelCase  )
	return tuple(string + word for word in suffixes  )







def 						SCREAMING_SNAKE_CASE(  )    ->    None:
	print(autocomplete_using_trie('de'  )  )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()









'''simple docstring'''


import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
						lowerCAmelCase__										= 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.",
						)

						lowerCAmelCase__										= parser.parse_args()

						lowerCAmelCase__										= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

						lowerCAmelCase__										= CLIPImageProcessor()
						lowerCAmelCase__										= CLIPVisionModelWithProjection.from_pretrained("openai/clip-vit-large-patch14")

						lowerCAmelCase__										= 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)






