





from __future__ import annotations




def _a   (    SCREAMING_SNAKE_CASE__     :    List[Any]  )			->							bool:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__  :     Dict           =		len(_lowerCAmelCase  )
							# We need to create solution object to save path.
							SCREAMING_SNAKE_CASE__  :     Optional[int]           =		[[0 for _ in range(_lowerCAmelCase  )] for _ in range(_lowerCAmelCase  )]
							SCREAMING_SNAKE_CASE__  :     Dict           =		run_maze(_lowerCAmelCase					, 0					, 0					, _lowerCAmelCase  )
							if solved:
														print("\n".join(str(_lowerCAmelCase  ) for row in solutions  )  )
							else:
														print("No solution exists!"  )
							return solved




def _a   (    SCREAMING_SNAKE_CASE__     :    Optional[Any]					, SCREAMING_SNAKE_CASE__     :    int					, SCREAMING_SNAKE_CASE__     :    Optional[Any]					, SCREAMING_SNAKE_CASE__     :    List[Any]  )			->							bool:

							'''simple docstring'''






							SCREAMING_SNAKE_CASE__  :     Dict           =		len(_lowerCAmelCase  )
							# Final check point.
							if i == j == (size - 1):
														SCREAMING_SNAKE_CASE__  :     Dict           =		1
														return True

							SCREAMING_SNAKE_CASE__  :     Optional[int]           =		(not i < 0) and (not j < 0)  # Check lower bounds
							SCREAMING_SNAKE_CASE__  :     Tuple           =		(i < size) and (j < size)  # Check upper bounds

							if lower_flag and upper_flag:
														# check for already visited and block points.
														SCREAMING_SNAKE_CASE__  :     Any           =		(not solutions[i][j]) and (not maze[i][j])
														if block_flag:
																					# check visited
																					SCREAMING_SNAKE_CASE__  :     Optional[int]           =		1

																					# check for directions
																					if (
																					    run_maze(_lowerCAmelCase					, i + 1					, _lowerCAmelCase					, _lowerCAmelCase  )
																					    or run_maze(_lowerCAmelCase					, _lowerCAmelCase					, j + 1					, _lowerCAmelCase  )
																					    or run_maze(_lowerCAmelCase					, i - 1					, _lowerCAmelCase					, _lowerCAmelCase  )
																					    or run_maze(_lowerCAmelCase					, _lowerCAmelCase					, j - 1					, _lowerCAmelCase  )
																					):
																												return True

																					SCREAMING_SNAKE_CASE__  :     List[Any]           =		0
																					return False
							return False


if __name__ == "__main__":
		import doctest

		doctest.testmod()











'''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_	(				_lowerCAmelCase			,_lowerCAmelCase			,_lowerCAmelCase			) -> int:
  __lowerCamelCase			:			Optional[Any]       			=					1.5
  __lowerCamelCase			:			Tuple       			=					int(factor * num_class_images			)
  __lowerCamelCase			:			Tuple       			=					ClipClient(
      url='https://knn.laion.ai/knn-service'			,indice_name='laion_400m'			,num_images=_lowerCAmelCase			,aesthetic_weight=0.1			)

  os.makedirs(F'{class_data_dir}/images'			,exist_ok=_lowerCAmelCase			)
  if len(list(Path(F'{class_data_dir}/images'			).iterdir()			)			) >= num_class_images:
    return

  while True:
    __lowerCamelCase			:			Dict       			=					client.query(text=_lowerCAmelCase			)
    if len(_lowerCAmelCase			) >= factor * num_class_images or num_images > 1E4:
      break
    else:
      __lowerCamelCase			:			Union[str, Any]       			=					int(factor * num_images			)
      __lowerCamelCase			:			List[str]       			=					ClipClient(
          url='https://knn.laion.ai/knn-service'			,indice_name='laion_400m'			,num_images=_lowerCAmelCase			,aesthetic_weight=0.1			,)

  __lowerCamelCase			:			List[Any]       			=					0
  __lowerCamelCase			:			Tuple       			=					0
  __lowerCamelCase			:			int       			=					tqdm(desc='downloading real regularization images'			,total=_lowerCAmelCase			)

  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:
      __lowerCamelCase			:			List[str]       			=					class_images[count]
      count += 1
      try:
        __lowerCamelCase			:			int       			=					requests.get(images['url']			)
        if img.status_code == 200:
          __lowerCamelCase			:			str       			=					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_	(				) -> Dict:
  __lowerCamelCase			:			Any       			=					argparse.ArgumentParser(''			,add_help=_lowerCAmelCase			)
  parser.add_argument('--class_prompt'			,help='text prompt to retrieve images'			,required=_lowerCAmelCase			,type=_lowerCAmelCase			)
  parser.add_argument('--class_data_dir'			,help='path to save images'			,required=_lowerCAmelCase			,type=_lowerCAmelCase			)
  parser.add_argument('--num_class_images'			,help='number of images to download'			,default=200			,type=_lowerCAmelCase			)
  return parser.parse_args()


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






