"""simple docstring"""







from datetime import datetime

import matplotlib.pyplot as plt
import torch
def 						__UpperCAmelCase       (					UpperCAmelCase_					:       Optional[int]						)							->    List[Any]:

	'''simple docstring'''





	for param in module.parameters():
		__snake_case    :							Optional[Any]   	=				False
def 						__UpperCAmelCase       (					)							->    Optional[int]:

	'''simple docstring'''





	__snake_case    :							List[Any]   	=				'cuda' if torch.cuda.is_available() else 'cpu'
	if torch.backends.mps.is_available() and torch.backends.mps.is_built():
		__snake_case    :							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 						__UpperCAmelCase       (					UpperCAmelCase_					:       Dict						)							->    List[Any]:

	'''simple docstring'''





	__snake_case    :							Optional[int]   	=				plt.imshow(UpperCAmelCase_						)
	fig.axes.get_xaxis().set_visible(UpperCAmelCase_						)
	fig.axes.get_yaxis().set_visible(UpperCAmelCase_						)
	plt.show()

def 						__UpperCAmelCase       (					)							->    List[str]:

	'''simple docstring'''





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






"""simple docstring"""







from abc import ABC, abstractmethod
from argparse import ArgumentParser

class 	UpperCamelCase    (					lowercase		):



				@staticmethod
				@abstractmethod
				def       _lowercase  (_A       :   ArgumentParser)					->			Tuple:
					raise NotImplementedError()






				@abstractmethod
				def       _lowercase  (self       :   Any)					->			Optional[Any]:
					raise NotImplementedError()





