
import requests




def 							a		(				snake_case__:   str		,  snake_case__:   str   ):


				'''simple docstring'''
				lowercase_	    =   {'''Content-Type''': '''application/json'''}
				lowercase_	    =   requests.post(snake_case__		,  json={'''text''': message_body}		,  headers=snake_case__   )
				if response.status_code != 200:
								lowercase_	    =   (
								    '''Request to slack returned an error '''
								    F'''{response.status_code}, the response is:\n{response.text}'''
								)
								raise ValueError(snake_case__   )


if __name__ == "__main__":
						# Set the slack url to the one provided by Slack when you create the webhook at
						# https://my.slack.com/services/new/incoming-webhook/
						send_slack_message('<YOUR MESSAGE BODY>', '<SLACK CHANNEL URL>')











import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
					A       :   List[Any]					= 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.''',
					)

					A       :   List[Any]					= parser.parse_args()

					A       :   int					= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

					A       :   Tuple					= CLIPImageProcessor()
					A       :   int					= CLIPVisionModelWithProjection.from_pretrained('''openai/clip-vit-large-patch14''')

					A       :   Tuple					= 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)



