


"""simple docstring"""






import operator as op


def __lowercase     (      lowerCamelCase_  :      Tuple  ):
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__     							=				lambda lowerCamelCase_						,					lowerCamelCase_  : int(x / y  )  # noqa: E731 integer division operation
				SCREAMING_SNAKE_CASE__     							=				{
				    "^": op.pow,
				    "*": op.mul,
				    "/": div,
				    "+": op.add,
				    "-": op.sub,
				}  # operators & their respective operation

				# print table header
				print("Symbol".center(8  )						,					"Action".center(12  )						,					"Stack"						,					sep=" | "  )
				print("-" * (30 + len(lowerCamelCase_  ))  )

				for x in post_fix:
								if x.isdigit():  # if x in digit
												stack.append(lowerCamelCase_  )  # append x to stack
												# output in tabular format
												print(x.rjust(8  )						,					("push(" + x + ")").ljust(12  )						,					",".join(lowerCamelCase_  )						,					sep=" | "  )
								else:
												SCREAMING_SNAKE_CASE__     							=				stack.pop()  # pop stack
												# output in tabular format
												print("".rjust(8  )						,					("pop(" + b + ")").ljust(12  )						,					",".join(lowerCamelCase_  )						,					sep=" | "  )

												SCREAMING_SNAKE_CASE__     							=				stack.pop()  # pop stack
												# output in tabular format
												print("".rjust(8  )						,					("pop(" + a + ")").ljust(12  )						,					",".join(lowerCamelCase_  )						,					sep=" | "  )

												stack.append(
												    str(opr[x](int(lowerCamelCase_  )						,					int(lowerCamelCase_  )  )  )  )  # evaluate the 2 values popped from stack & push result to stack
												# output in tabular format
												print(
												    x.rjust(8  )						,					("push(" + a + x + b + ")").ljust(12  )						,					",".join(lowerCamelCase_  )						,					sep=" | "						,					)

				return int(stack[0]  )


if __name__ == "__main__":
	_lowerCamelCase     =  input('\n\nEnter a Postfix Equation (space separated) = ').split(' ')
	print('\n\tResult = ', solve(Postfix))








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


class 			lowerCamelCase_		:





				"""simple docstring"""







				def __init__(						self     ):
								SCREAMING_SNAKE_CASE__     							=				WATERMARK_BITS
								SCREAMING_SNAKE_CASE__     							=				WatermarkEncoder()

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






				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__     ):
								# can't encode images that are smaller than 256
								if images.shape[-1] < 256:
												return images

								SCREAMING_SNAKE_CASE__     							=				(255 * (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 / 255 - 0.5)       ,		min=-1.0       ,		max=1.0     )
								return images
