


"""simple docstring"""







import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__lowercase    					=      0B1011_0011_1110_1100_1001_0000_0111_1011_1011_0001_1001_1110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
__lowercase    					=      [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]






class 						_A  :







    """simple docstring"""




    def __init__(					self				:    Tuple):
      a						:		List[str]      							=			WATERMARK_BITS
      a						:		int      							=			WatermarkEncoder()

      self.encoder.set_watermark("bits"				, self.watermark)






    def 	__snake_case							(					self				:    int				, __UpperCAmelCase				:    torch.FloatTensor):
      # can't encode images that are smaller than 256
      if images.shape[-1] < 256:
        return images

      a						:		Optional[Any]      							=			(255 * (images / 2 + 0.5)).cpu().permute(0				, 2				, 3				, 1).float().numpy()

      a						:		str      							=			[self.encoder.encode(__UpperCAmelCase				, "dwtDct") for image in images]

      a						:		Any      							=			torch.from_numpy(np.array(__UpperCAmelCase)).permute(0				, 3				, 1				, 2)

      a						:		Any      							=			torch.clamp(2 * (images / 255 - 0.5)				, min=-1.0				, max=1.0)
      return images









from __future__ import annotations

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    dict	,     SCREAMING_SNAKE_CASE_		:    str			):



     '''simple docstring'''





     lowercase__      , lowercase__    :   List[str]      =       set(SCREAMING_SNAKE_CASE_			), [start]

     while stack:
          lowercase__    :   Union[str, Any]      =       stack.pop()
          explored.add(SCREAMING_SNAKE_CASE_			)
          # Differences from BFS:
          # 1) pop last element instead of first one
          # 2) add adjacent elements to stack without exploring them
          for adj in reversed(graph[v]			):
               if adj not in explored:
                    stack.append(SCREAMING_SNAKE_CASE_			)
     return explored


snake_case_			  = {
    '''A''': ['''B''', '''C''', '''D'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F'''],
    '''D''': ['''B''', '''D'''],
    '''E''': ['''B''', '''F'''],
    '''F''': ['''C''', '''E''', '''G'''],
    '''G''': ['''F'''],
}

if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(depth_first_search(G, '''A'''))

