




"""simple docstring"""

def 		_snake_case	(   _snake_case				:   str							,    _snake_case				:   int				)       ->   str:






      '''simple docstring'''


      _A     =  [[] for _ in range(_snake_case				)]
      _A     =  key - 1

      if key <= 0:
            raise ValueError('Height of grid can\'t be 0 or negative'				)
      if key == 1 or len(_snake_case				) <= key:
            return input_string

      for position, character in enumerate(_snake_case				):
            _A     =  position % (lowest * 2)  # puts it in bounds
            _A     =  min(_snake_case							,    lowest * 2 - num				)  # creates zigzag pattern
            temp_grid[num].append(_snake_case				)
      _A     =  [''.join(_snake_case				) for row in temp_grid]
      _A     =  ''.join(_snake_case				)

      return output_string






def 		_snake_case	(   _snake_case				:   str							,    _snake_case				:   int				)       ->   str:






      '''simple docstring'''


      _A     =  []
      _A     =  key - 1

      if key <= 0:
            raise ValueError('Height of grid can\'t be 0 or negative'				)
      if key == 1:
            return input_string

      _A     =  [[] for _ in range(_snake_case				)]  # generates template
      for position in range(len(_snake_case				)				):
            _A     =  position % (lowest * 2)  # puts it in bounds
            _A     =  min(_snake_case							,    lowest * 2 - num				)  # creates zigzag pattern
            temp_grid[num].append('*'				)

      _A     =  0
      for row in temp_grid:  # fills in the characters
            _A     =  input_string[counter : counter + len(_snake_case				)]
            grid.append(list(_snake_case				)				)
            counter += len(_snake_case				)

      _A     =  ''  # reads as zigzag
      for position in range(len(_snake_case				)				):
            _A     =  position % (lowest * 2)  # puts it in bounds
            _A     =  min(_snake_case							,    lowest * 2 - num				)  # creates zigzag pattern
            output_string += grid[num][0]
            grid[num].pop(0				)
      return output_string






def 		_snake_case	(   _snake_case				:   str				)       ->   dict[int, str]:






      '''simple docstring'''


      _A     =  {}
      for key_guess in range(1							,    len(_snake_case				)				):  # tries every key
            _A     =  decrypt(_snake_case							,    _snake_case				)
      return results


if __name__ == "__main__":
       import doctest

       doctest.testmod()







"""simple docstring"""

from datetime import datetime

import matplotlib.pyplot as plt
import torch






def 		_snake_case	(   _snake_case				:   Dict				)       ->   Optional[Any]:






      '''simple docstring'''


      for param in module.parameters():
            _A     =  False






def 		_snake_case	(   )       ->   Tuple:






      '''simple docstring'''


      _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 		_snake_case	(   _snake_case				:   Dict				)       ->   Optional[Any]:






      '''simple docstring'''


      _A     =  plt.imshow(_snake_case				)
      fig.axes.get_xaxis().set_visible(_snake_case				)
      fig.axes.get_yaxis().set_visible(_snake_case				)
      plt.show()







def 		_snake_case	(   )       ->   Optional[Any]:






      '''simple docstring'''


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

