





def     _UpperCamelCase     (a__   :str = "The quick brown fox jumps over the lazy dog"   ,			):






							"""simple docstring"""





							UpperCamelCase__				     =			set()

							# Replace all the whitespace in our sentence
							UpperCamelCase__				     =			input_str.replace(""" """   ,			""""""       )
							for alpha in input_str:
														if "a" <= alpha.lower() <= "z":
																					frequency.add(alpha.lower()       )
							return len(a__       ) == 26





def     _UpperCamelCase     (a__   :str = "The quick brown fox jumps over the lazy dog"   ,			):






							"""simple docstring"""





							UpperCamelCase__				     =			[False] * 26
							for char in input_str:
														if char.islower():
																					UpperCamelCase__				     =			True
														elif char.isupper():
																					UpperCamelCase__				     =			True
							return all(a__       )





def     _UpperCamelCase     (a__   :str = "The quick brown fox jumps over the lazy dog"   ,			):






							"""simple docstring"""





							return len({char for char in input_str.lower() if char.isalpha()}       ) == 26





def     _UpperCamelCase     ():






							"""simple docstring"""





							from timeit import timeit

							UpperCamelCase__				     =			"""from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"""
							print(timeit("""is_pangram()"""   ,			setup=a__       )       )
							print(timeit("""is_pangram_faster()"""   ,			setup=a__       )       )
							print(timeit("""is_pangram_fastest()"""   ,			setup=a__       )       )
							# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
							# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					benchmark()











import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
					UpperCamelCase__											= 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.",
					)

					UpperCamelCase__											= parser.parse_args()

					UpperCamelCase__											= UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

					UpperCamelCase__											= CLIPImageProcessor()
					UpperCamelCase__											= CLIPVisionModelWithProjection.from_pretrained("openai/clip-vit-large-patch14")

					UpperCamelCase__											= 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)




