


"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path

import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm







def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			List[Any]:
							snake_case_          =						1.5
							snake_case_          =						int(factor * num_class_images			)
							snake_case_          =						ClipClient(
							    url="""https://knn.laion.ai/knn-service"""			,	indice_name="""laion_400m"""			,	num_images=_SCREAMING_SNAKE_CASE			,	aesthetic_weight=0.1			)

							os.makedirs(f"""{class_data_dir}/images"""			,	exist_ok=_SCREAMING_SNAKE_CASE			)
							if len(list(Path(f"""{class_data_dir}/images"""			).iterdir()			)			) >= num_class_images:
														return

							while True:
														snake_case_          =						client.query(text=_SCREAMING_SNAKE_CASE			)
														if len(_SCREAMING_SNAKE_CASE			) >= factor * num_class_images or num_images > 1E4:
																					break
														else:
																					snake_case_          =						int(factor * num_images			)
																					snake_case_          =						ClipClient(
																					    url="""https://knn.laion.ai/knn-service"""			,	indice_name="""laion_400m"""			,	num_images=_SCREAMING_SNAKE_CASE			,	aesthetic_weight=0.1			,	)

							snake_case_          =						0
							snake_case_          =						0
							snake_case_          =						tqdm(desc="""downloading real regularization images"""			,	total=_SCREAMING_SNAKE_CASE			)

							with open(f"""{class_data_dir}/caption.txt"""			,	"""w"""			) as fa, open(f"""{class_data_dir}/urls.txt"""			,	"""w"""			) as fa, open(
							    f"""{class_data_dir}/images.txt"""			,	"""w"""			) as fa:
														while total < num_class_images:
																					snake_case_          =						class_images[count]
																					count += 1
																					try:
																												snake_case_          =						requests.get(images["""url"""]			)
																												if img.status_code == 200:
																																			snake_case_          =						Image.open(BytesIO(img.content			)			)
																																			with open(f"""{class_data_dir}/images/{total}.jpg"""			,	"""wb"""			) as f:
																																										f.write(img.content			)
																																			fa.write(images["""caption"""] + """\n"""			)
																																			fa.write(images["""url"""] + """\n"""			)
																																			fa.write(f"""{class_data_dir}/images/{total}.jpg""" + """\n"""			)
																																			total += 1
																																			pbar.update(1			)
																												else:
																																			continue
																					except Exception:
																												continue
							return







def   _a			( )      ->			Optional[Any]:
							snake_case_          =						argparse.ArgumentParser(""""""			,	add_help=_SCREAMING_SNAKE_CASE			)
							parser.add_argument("""--class_prompt"""			,	help="""text prompt to retrieve images"""			,	required=_SCREAMING_SNAKE_CASE			,	type=_SCREAMING_SNAKE_CASE			)
							parser.add_argument("""--class_data_dir"""			,	help="""path to save images"""			,	required=_SCREAMING_SNAKE_CASE			,	type=_SCREAMING_SNAKE_CASE			)
							parser.add_argument("""--num_class_images"""			,	help="""number of images to download"""			,	default=200			,	type=_SCREAMING_SNAKE_CASE			)
							return parser.parse_args()


if __name__ == "__main__":
				__SCREAMING_SNAKE_CASE							:      Dict						=      parse_args()
				retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)







"""simple docstring"""
def   _a			( _SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			)      ->			str:
							return "\n".join(
							    f"""{number} * {i} = {number * i}""" for i in range(1			,	number_of_terms + 1			)			)


if __name__ == "__main__":
				print(multiplication_table(number=5, number_of_terms=10))



