

from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands



def   __UpperCAmelCase					(      )     ->	List[str]:

					"""simple docstring"""

					_a      :       Optional[int]   =						ArgumentParser('''Transformers CLI tool'''						,usage='''transformers-cli <command> [<args>]'''      )
					_a      :       Any   =						parser.add_subparsers(help='''transformers-cli command helpers'''      )

					# Register commands
					ConvertCommand.register_subcommand(__a      )
					DownloadCommand.register_subcommand(__a      )
					EnvironmentCommand.register_subcommand(__a      )
					RunCommand.register_subcommand(__a      )
					ServeCommand.register_subcommand(__a      )
					UserCommands.register_subcommand(__a      )
					AddNewModelCommand.register_subcommand(__a      )
					AddNewModelLikeCommand.register_subcommand(__a      )
					LfsCommands.register_subcommand(__a      )
					PTtoTFCommand.register_subcommand(__a      )

					# Let's go
					_a      :       str   =						parser.parse_args()

					if not hasattr(__a						,'''func'''      ):
										parser.print_help()
										exit(1      )

					# Run
					_a      :       str   =						args.func(__a      )
					service.run()


if __name__ == "__main__":
			main()







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)





