"""simple docstring"""







from datetime import datetime

import matplotlib.pyplot as plt
import torch



def 			lowercase__(       __SCREAMING_SNAKE_CASE							:     str      ):
     for param in module.parameters():
          lowercase_	:				str													=	False



def 			lowercase__(       ):
     lowercase_	:				Optional[Any]													=	'cuda' if torch.cuda.is_available() else 'cpu'
     if torch.backends.mps.is_available() and torch.backends.mps.is_built():
          lowercase_	:				str													=	'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 			lowercase__(       __SCREAMING_SNAKE_CASE							:     Optional[int]      ):
     lowercase_	:				int													=	plt.imshow(_lowerCamelCase      )
     fig.axes.get_xaxis().set_visible(_lowerCamelCase      )
     fig.axes.get_yaxis().set_visible(_lowerCamelCase      )
     plt.show()







def 			lowercase__(       ):
     lowercase_	:				List[Any]													=	datetime.now()
     lowercase_	:				List[Any]													=	current_time.strftime('%H:%M:%S'      )
     return timestamp








'''simple docstring'''

import functools





def 						UpperCamelCase				(							_lowerCamelCase					:					str						,       _lowerCamelCase					:					str       ):
    A__				=			len(_lowerCamelCase       )
    A__				=			len(_lowerCamelCase       )

    @functools.cache
    def min_distance(_lowerCamelCase					:					int						,       _lowerCamelCase					:					int       ) -> int:
        # if first word index is overflow - delete all from the second word
        if indexa >= len_worda:
            return len_worda - indexa
        # if second word index is overflow - delete all from the first word
        if indexa >= len_worda:
            return len_worda - indexa
        A__				=			int(worda[indexa] != worda[indexa]       )  # current letters not identical
        return min(
            1 + min_distance(indexa + 1						,       _lowerCamelCase       )						,       1 + min_distance(_lowerCamelCase						,       indexa + 1       )						,       diff + min_distance(indexa + 1						,       indexa + 1       )						,       )

    return min_distance(0						,       0       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()



