


"""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
a__    :							Dict            =					0B10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_11_10_11_00_01_10_01_11_10
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
a__    :							Tuple            =					[int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]




class 			UpperCamelCase_     :

	"""simple docstring"""





	def __init__(			self      :    int       )	->     Any:
						__SCREAMING_SNAKE_CASE						       =    WATERMARK_BITS
						__SCREAMING_SNAKE_CASE						       =    WatermarkEncoder()

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




	def   UpperCAmelCase_				(			self      :    Union[str, Any]      ,      UpperCAmelCase__      :    torch.FloatTensor       )	->     Union[str, Any]:
						# can't encode images that are smaller than 256
						if images.shape[-1] < 2_5_6:
											return images

						__SCREAMING_SNAKE_CASE						       =    (2_5_5 * (images / 2 + 0.5)).cpu().permute(0      ,      2      ,      3      ,      1       ).float().numpy()

						__SCREAMING_SNAKE_CASE						       =    [self.encoder.encode(UpperCAmelCase__      ,      "dwtDct"       ) for image in images]

						__SCREAMING_SNAKE_CASE						       =    torch.from_numpy(np.array(UpperCAmelCase__       )       ).permute(0      ,      3      ,      1      ,      2       )

						__SCREAMING_SNAKE_CASE						       =    torch.clamp(2 * (images / 2_5_5 - 0.5)      ,      min=-1.0      ,      max=1.0       )
						return images




"""simple docstring"""







def        UpperCAmelCase__	(lowerCAmelCase_  ,						lowerCAmelCase_       ):




					'''simple docstring'''


					if digit_amount > 0:
										return round(number - int(lowerCAmelCase_       )  ,						lowerCAmelCase_       )
					return number - int(lowerCAmelCase_       )


if __name__ == "__main__":
		print(decimal_isolate(1.53, 0))
		print(decimal_isolate(35.3_45, 1))
		print(decimal_isolate(35.3_45, 2))
		print(decimal_isolate(35.3_45, 3))
		print(decimal_isolate(-14.7_89, 3))
		print(decimal_isolate(0, 2))
		print(decimal_isolate(-14.1_23, 1))
		print(decimal_isolate(-14.1_23, 2))
		print(decimal_isolate(-14.1_23, 3))
