




'''simple docstring'''



from datetime import datetime

import matplotlib.pyplot as plt
import torch







def       _UpperCamelCase			(_lowerCamelCase				:  int						)-> List[Any]:




     '''simple docstring'''





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







def       _UpperCamelCase			()-> List[str]:




     '''simple docstring'''





     __snake_case            =	'''cuda''' if torch.cuda.is_available() else '''cpu'''
     if torch.backends.mps.is_available() and torch.backends.mps.is_built():
          __snake_case            =	'''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       _UpperCamelCase			(_lowerCamelCase				:  Any						)-> Optional[Any]:




     '''simple docstring'''





     __snake_case            =	plt.imshow(_lowerCamelCase						)
     fig.axes.get_xaxis().set_visible(_lowerCamelCase						)
     fig.axes.get_yaxis().set_visible(_lowerCamelCase						)
     plt.show()







def       _UpperCamelCase			()-> List[Any]:




     '''simple docstring'''





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












'''simple docstring'''



def       _UpperCamelCase			(_lowerCamelCase				:  int ,						_lowerCamelCase				:  int ,						_lowerCamelCase				:  int						)-> float:




     '''simple docstring'''





     __snake_case            =	(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
     # formula for sum of series
     return total







def       _UpperCamelCase			()-> str:




     '''simple docstring'''





     print(sum_of_series(1 ,						1 ,						10						)						)


if __name__ == "__main__":
     import doctest

     doctest.testmod()






