
from argparse import ArgumentParser

from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.utils.logging import set_verbosity_info




def 			_SCREAMING_SNAKE_CASE      (	_lowerCamelCase				:    Optional[Any])      ->					Any:






							'''simple docstring'''





							return {key.lstrip("-"): value for key, value in zip(unknown_args[::2]		,						unknown_args[1::2])}




def 			_SCREAMING_SNAKE_CASE      (	)      ->					Dict:






							'''simple docstring'''





							__UpperCamelCase			:     Optional[int]         =      ArgumentParser(
							    "HuggingFace Datasets CLI tool"		,						usage="datasets-cli <command> [<args>]"		,						allow_abbrev=_lowerCamelCase)
							__UpperCamelCase			:     str         =      parser.add_subparsers(help="datasets-cli command helpers")
							set_verbosity_info()

							# Register commands
							ConvertCommand.register_subcommand(_lowerCamelCase)
							EnvironmentCommand.register_subcommand(_lowerCamelCase)
							TestCommand.register_subcommand(_lowerCamelCase)
							RunBeamCommand.register_subcommand(_lowerCamelCase)
							DummyDataCommand.register_subcommand(_lowerCamelCase)

							# Parse args
							__UpperCamelCase     ,		__UpperCamelCase			:     Dict         =      parser.parse_known_args()
							if not hasattr(_lowerCamelCase		,						"func"):
														parser.print_help()
														exit(1)
							__UpperCamelCase			:     Tuple         =      parse_unknown_args(_lowerCamelCase)

							# Run
							__UpperCamelCase			:     int         =      args.func(_lowerCamelCase		,						**_lowerCamelCase)
							service.run()


if __name__ == "__main__":
		main()

import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
		lowercase						:      List[str]									= 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.',
		)

		lowercase						:      int									= parser.parse_args()

		lowercase						:      str									= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

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

		lowercase						:      int									= 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)