

'''simple docstring'''


def 	_a       (				__lowerCAmelCase		:      Dict     ):

		"""simple docstring"""

		stooge(__lowerCAmelCase   ,							0   ,							len(__lowerCAmelCase     ) - 1     )
		return arr




def 	_a       (				__lowerCAmelCase		:      List[Any]   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      str     ):

		"""simple docstring"""

		if i >= h:
				return

		# If first element is smaller than the last then swap them
		if arr[i] > arr[h]:
				snake_case__						,       snake_case__						:       Tuple       						=  arr[h], arr[i]

		# If there are more than 2 elements in the array
		if h - i + 1 > 2:
				snake_case__						:       Any       						=  (int)((h - i + 1) / 3     )

				# Recursively sort first 2/3 elements
				stooge(__lowerCAmelCase   ,							__lowerCAmelCase   ,							(h - t)     )

				# Recursively sort last 2/3 elements
				stooge(__lowerCAmelCase   ,							i + t   ,							(__lowerCAmelCase)     )

				# Recursively sort first 2/3 elements
				stooge(__lowerCAmelCase   ,							__lowerCAmelCase   ,							(h - t)     )


if __name__ == "__main__":
					lowerCAmelCase__						:       Union[str, Any]										=						input("""Enter numbers separated by a comma:\n""").strip()
					lowerCAmelCase__						:       Union[str, Any]										=						[int(item) for item in user_input.split(""",""")]
					print(stooge_sort(unsorted))






'''simple docstring'''


import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
					lowerCAmelCase__						:       Dict										=						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__						:       List[Any]										=						parser.parse_args()

					lowerCAmelCase__						:       Optional[Any]										=						UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

					lowerCAmelCase__						:       Optional[int]										=						CLIPImageProcessor()
					lowerCAmelCase__						:       str										=						CLIPVisionModelWithProjection.from_pretrained("""openai/clip-vit-large-patch14""")

					lowerCAmelCase__						:       Dict										=						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)



