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
lowerCamelCase_    :		List[Any]							=	0b101_100_111_110_110_010_010_000_011_110_111_011_000_110_011_110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
lowerCamelCase_    :		List[str]							=	[int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]


class 						a__							:



			def __init__(						self   )			->   Union[str, Any]:
								__a		 =       WATERMARK_BITS
								__a		 =       WatermarkEncoder()

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







			def __SCREAMING_SNAKE_CASE							(						self				,						UpperCAmelCase   )			->   int:
								# can't encode images that are smaller than 256
								if images.shape[-1] < 2_5_6:
													return images

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

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

								__a		 =       torch.from_numpy(np.array(UpperCAmelCase   )   ).permute(0				,						3				,						1				,						2   )

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





from datetime import datetime

import matplotlib.pyplot as plt
import torch
def 							lowerCAmelCase(     __lowerCamelCase						):
					for param in module.parameters():
										__a		 =       False
def 							lowerCAmelCase(     ):
					__a		 =       'cuda' if torch.cuda.is_available() else 'cpu'
					if torch.backends.mps.is_available() and torch.backends.mps.is_built():
										__a		 =       'mps'
					if device == "mps":
										print(
										    'WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'
										    ' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'
										    ' with generations.'						)
					return device
def 							lowerCAmelCase(     __lowerCamelCase						):
					__a		 =       plt.imshow(__lowerCamelCase						)
					fig.axes.get_xaxis().set_visible(__lowerCamelCase						)
					fig.axes.get_yaxis().set_visible(__lowerCamelCase						)
					plt.show()



def 							lowerCAmelCase(     ):
					__a		 =       datetime.now()
					__a		 =       current_time.strftime('%H:%M:%S'						)
					return timestamp




