





"""simple docstring"""






def      __A   (      a_    :int)		->		int:
				__a			:    list[list[int]]      							=	[[0 for _ in range(a_)] for _ in range(m + 1)]
				for i in range(m + 1):
								__a			:    int      							=	1

				for n in range(m + 1):
								for k in range(1 ,							a_):
												memo[n][k] += memo[n][k - 1]
												if n - k > 0:
																memo[n][k] += memo[n - k - 1][k]

				return memo[m][m - 1]


if __name__ == "__main__":
		import sys

		if len(sys.argv) == 1:
				try:
						A			      =	int(input('''Enter a number: ''').strip())
						print(partition(n))
				except ValueError:
						print('''Please enter a number.''')
		else:
				try:
						A			      =	int(sys.argv[1])
						print(partition(n))
				except ValueError:
						print('''Please pass a number.''')



'''simple docstring'''
import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


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

		__snake_case				 =	parser.parse_args()

		__snake_case				 =	UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

		__snake_case				 =	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)