





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
snake_case_           =      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
snake_case_           =      [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]

class 		SCREAMING_SNAKE_CASE__    :


      def __init__(self	:				Dict				):





         """simple docstring"""



         __snake_case								=       WATERMARK_BITS
         __snake_case								=       WatermarkEncoder()

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


      def        a			(self	:				Optional[int]    ,      a__	:				torch.FloatTensor				):





         """simple docstring"""



         if images.shape[-1] < 256:
            return images

         __snake_case								=       (255 * (images / 2 + 0.5)).cpu().permute(0    ,      2    ,      3    ,      1				).float().numpy()

         __snake_case								=       [self.encoder.encode(a__    ,      '''dwtDct'''				) for image in images]

         __snake_case								=       torch.from_numpy(np.array(a__				)				).permute(0    ,      3    ,      1    ,      2				)

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








class 		SCREAMING_SNAKE_CASE__    :


      def __init__(self	:				str    ,      a__	:				list				):





         """simple docstring"""



         __snake_case								=       set_counts
         __snake_case								=       max(a__				)
         __snake_case								=       len(a__				)
         __snake_case								=       [1] * num_sets
         __snake_case								=       list(range(a__				)				)


      def        a			(self	:				str    ,      a__	:				int    ,      a__	:				int				):





         """simple docstring"""



         __snake_case								=       self.get_parent(a__				)
         __snake_case								=       self.get_parent(a__				)

         if src_parent == dst_parent:
            return False

         if self.ranks[dst_parent] >= self.ranks[src_parent]:
            self.set_counts[dst_parent] += self.set_counts[src_parent]
            __snake_case								=       0
            __snake_case								=       dst_parent
            if self.ranks[dst_parent] == self.ranks[src_parent]:
               self.ranks[dst_parent] += 1
            __snake_case								=       self.set_counts[dst_parent]
         else:
            self.set_counts[src_parent] += self.set_counts[dst_parent]
            __snake_case								=       0
            __snake_case								=       src_parent
            __snake_case								=       self.set_counts[src_parent]

         __snake_case								=       max(self.max_set    ,      a__				)
         return True


      def        a			(self	:				Union[str, Any]    ,      a__	:				int				):





         """simple docstring"""



         if self.parents[disj_set] == disj_set:
            return disj_set
         __snake_case								=       self.get_parent(self.parents[disj_set]				)
         return self.parents[disj_set]

