
'''simple docstring'''
def      UpperCamelCase_				(      A__						):

	def merge(A__  ,      A__						) -> list:

		def _merge():
			while left and right:
				yield (left if left[0] <= right[0] else right).pop(0						)
			yield from left
			yield from right

		return list(_merge()						)

	if len(A__						) <= 1:
		return collection
	a_      				=						len(A__						) // 2
	return merge(merge_sort(collection[:mid]						)  ,      merge_sort(collection[mid:]						)						)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		lowercase__											=input('Enter numbers separated by a comma:\n').strip()
		lowercase__											=[int(item) for item in user_input.split(',')]
		print(*merge_sort(unsorted), sep=',')


'''simple docstring'''
import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
		lowercase__											=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.',
		)

		lowercase__											=parser.parse_args()

		lowercase__											=UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

		lowercase__											=CLIPImageProcessor()
		lowercase__											=CLIPVisionModelWithProjection.from_pretrained('openai/clip-vit-large-patch14')

		lowercase__											=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)
