



"""simple docstring"""


from PIL import Image

def  _lowerCAmelCase      (   lowercase_		,	lowercase_						):
						UpperCAmelCase             = (259 * (level + 255)) / (255 * (259 - level))

						def contrast(lowercase_						) -> int:
												return int(128 + factor * (c - 128)						)

						return img.point(lowercase_						)


if __name__ == "__main__":
				# Load image
				with Image.open("""image_data/lena.jpg""") as img:
								# Change contrast to 170
								snake_case_				     =       change_contrast(img, 170)
								cont_img.save("""image_data/lena_high_contrast.png""", format="""png""")









'''simple docstring'''
from datetime import datetime

import matplotlib.pyplot as plt
import torch


def 			a      (			__a   )  ->	int:



					'''simple docstring'''






					for param in module.parameters():
										UpperCamelCase__   :Dict												= False


def 			a      (			)  ->	Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__   :List[Any]												= '''cuda''' if torch.cuda.is_available() else '''cpu'''
					if torch.backends.mps.is_available() and torch.backends.mps.is_built():
										UpperCamelCase__   :Optional[int]												= '''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 			a      (			__a   )  ->	Any:



					'''simple docstring'''






					UpperCamelCase__   :Dict												= plt.imshow(__a   )
					fig.axes.get_xaxis().set_visible(__a   )
					fig.axes.get_yaxis().set_visible(__a   )
					plt.show()







def 			a      (			)  ->	str:



					'''simple docstring'''






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