




from typing import List

import PIL
import torch
from PIL import Image

from ...configuration_utils import ConfigMixin
from ...models.modeling_utils import ModelMixin
from ...utils import PIL_INTERPOLATION




class 	UpperCamelCase__			(lowerCAmelCase__					,       lowerCAmelCase__  ):

    '''simple docstring'''



    def __init__(					self  )  ->   List[str]:
           super().__init__()

           self.register_buffer("watermark_image"  ,						torch.zeros((62, 62, 4)  )  )
           lowerCamelCase     :   Any    				=      None







    def 					_lowercase  (					self  ,						UpperCamelCase__  ,						UpperCamelCase__=None  )  ->   List[Any]:
           # copied from https://github.com/deep-floyd/IF/blob/b77482e36ca2031cb94dbca1001fc1e6400bf4ab/deepfloyd_if/modules/base.py#L287

           lowerCamelCase     :   Optional[int]    				=      images[0].height
           lowerCamelCase     :   List[Any]    				=      images[0].width

           lowerCamelCase     :   Dict    				=      sample_size or h

           lowerCamelCase     :   Optional[Any]    				=      min(h / sample_size  ,						w / sample_size  )
           lowerCamelCase     :   int    				=      (int(h / coef  ), int(w / coef  )) if coef < 1 else (h, w)

           lowerCamelCase     :   Tuple    				=      1024**2, img_w * img_h
           lowerCamelCase     :   str    				=      (Sa / Sa) ** 0.5
           lowerCamelCase     :   str    				=      int(K * 62  ), img_w - int(14 * K  ), img_h - int(14 * K  )

           if self.watermark_image_as_pil is None:
                  lowerCamelCase     :   Optional[int]    				=      self.watermark_image.to(torch.uinta  ).cpu().numpy()
                  lowerCamelCase     :   Union[str, Any]    				=      Image.fromarray(UpperCamelCase__  ,						mode="RGBA"  )
                  lowerCamelCase     :   Union[str, Any]    				=      watermark_image

           lowerCamelCase     :   Tuple    				=      self.watermark_image_as_pil.resize(
               (wm_size, wm_size)  ,						PIL_INTERPOLATION["bicubic"]  ,						reducing_gap=UpperCamelCase__  )

           for pil_img in images:
                  pil_img.paste(UpperCamelCase__  ,						box=(wm_x - wm_size, wm_y - wm_size, wm_x, wm_y)  ,						mask=wm_img.split()[-1]  )

           return images












from itertools import compress, repeat
from math import ceil, sqrt

def   A   (   _SCREAMING_SNAKE_CASE					)			->				list[int]:

       if num <= 2:
              return []
       if num == 3:
              return [2]

       # Odd sieve for numbers in range [3, num - 1]
       lowerCamelCase     :   str    				=      bytearray(B"\x01"					) * ((num >> 1) - 1)

       for i in range(3				,int(sqrt(_SCREAMING_SNAKE_CASE					)					) + 1				,2					):
              if sieve[(i >> 1) - 1]:
                     lowerCamelCase     :   Tuple    				=      i**2
                     lowerCamelCase     :   str    				=      repeat(
                         0				,ceil((num - i_squared) / (i << 1)					)					)

       return [2] + list(compress(range(3				,_SCREAMING_SNAKE_CASE				,2					)				,_SCREAMING_SNAKE_CASE					)					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()






