

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

class 			a					:


						def __init__(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[Any]							=      WATERMARK_BITS
										_UpperCAmelCase    :						Any							=      WatermarkEncoder()

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





						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


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

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

										_UpperCAmelCase    :						Tuple							=      [self.encoder.encode(_lowerCamelCase  ,   "dwtDct"		) for image in images]

										_UpperCAmelCase    :						List[Any]							=      torch.from_numpy(np.array(_lowerCamelCase		)		).permute(0  ,   3  ,   1  ,   2		)

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





from typing import Any

class 			a					:


						def __init__(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						List[Any]							=      data
										_UpperCAmelCase    :						Any							=      None







class 			a					:


						def __init__(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						Union[str, Any]							=      None


						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										_UpperCAmelCase    :						str							=      self.head
										while temp is not None:
														print(temp.data  ,   end=" "		)
														_UpperCAmelCase    :						str							=      temp.next
										print()


						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						Optional[int]							=      Node(A_		)
										_UpperCAmelCase    :						Tuple							=      self.head
										_UpperCAmelCase    :						Tuple							=      new_node





						def     _UpperCAmelCase			(    self  ,   A_  ,   A_		):







										'''simple docstring'''


										if node_data_a == node_data_a:
														return
										else:
														_UpperCAmelCase    :						int							=      self.head
														while node_a is not None and node_a.data != node_data_a:
																		_UpperCAmelCase    :						Tuple							=      node_a.next

														_UpperCAmelCase    :						Dict							=      self.head
														while node_a is not None and node_a.data != node_data_a:
																		_UpperCAmelCase    :						List[Any]							=      node_a.next

														if node_a is None or node_a is None:
																		return

														_UpperCAmelCase						,							_UpperCAmelCase    :						Optional[int]							=      node_a.data, node_a.data


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE_            = LinkedList()
					for i in range(5, 0, -1):
										ll.push(i)

					ll.print_list()

					ll.swap_nodes(1, 4)
					print('After swapping')
					ll.print_list()


