





"""simple docstring"""


def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		List[str]				   =			len(SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		Dict				   =			len(matrix[0]     )
						UpperCamelCase				:		str				   =			min(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

						for row in range(SCREAMING_SNAKE_CASE     ):
												# Check if diagonal element is not zero
												if matrix[row][row] != 0:
																		# Eliminate all the elements below the diagonal
																		for col in range(row + 1							,     SCREAMING_SNAKE_CASE     ):
																								UpperCamelCase				:		List[Any]				   =			matrix[col][row] / matrix[row][row]
																								for i in range(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
																														matrix[col][i] -= multiplier * matrix[row][i]
												else:
																		# Find a non-zero diagonal element to swap rows
																		UpperCamelCase				:		Union[str, Any]				   =			True
																		for i in range(row + 1							,     SCREAMING_SNAKE_CASE     ):
																								if matrix[i][row] != 0:
																														UpperCamelCase   ,						UpperCamelCase				:		Union[str, Any]				   =			matrix[i], matrix[row]
																														UpperCamelCase				:		Any				   =			False
																														break
																		if reduce:
																								rank -= 1
																								for i in range(SCREAMING_SNAKE_CASE     ):
																														UpperCamelCase				:		Dict				   =			matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
																		row -= 1

						return rank


if __name__ == "__main__":
		import doctest

		doctest.testmod()







import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
      snake_case__				:	Optional[int]					       =					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__				:	Tuple					       =					parser.parse_args()

      snake_case__				:	Dict					       =					UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

      snake_case__				:	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)





