
"""simple docstring"""


import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
		_lowercase				 =					{
		    """linear""": PIL.Image.Resampling.BILINEAR,
		    """bilinear""": PIL.Image.Resampling.BILINEAR,
		    """bicubic""": PIL.Image.Resampling.BICUBIC,
		    """lanczos""": PIL.Image.Resampling.LANCZOS,
		    """nearest""": PIL.Image.Resampling.NEAREST,
		}
else:
		_lowercase				 =					{
		    """linear""": PIL.Image.LINEAR,
		    """bilinear""": PIL.Image.BILINEAR,
		    """bicubic""": PIL.Image.BICUBIC,
		    """lanczos""": PIL.Image.LANCZOS,
		    """nearest""": PIL.Image.NEAREST,
		}






def    _snake_case					(		snake_case__ :  Optional[Any]  ):
	A     = (images / 2 + 0.5).clamp(0						,   1  )
	A     = images.cpu().permute(0						,   2						,   3						,   1  ).float().numpy()
	A     = numpy_to_pil(__lowerCAmelCase  )
	return images






def    _snake_case					(		snake_case__ :  Optional[int]  ):
	if images.ndim == 3:
		A     = images[None, ...]
	A     = (images * 255).round().astype('uint8'  )
	if images.shape[-1] == 1:
		# special case for grayscale (single channel) images
		A     = [Image.fromarray(image.squeeze()						,   mode='L'  ) for image in images]
	else:
		A     = [Image.fromarray(__lowerCAmelCase  ) for image in images]

	return pil_images




from __future__ import annotations

import numpy as np

def        __a			(   __lowerCAmelCase   )     ->     Optional[Any]:
					return np.maximum(0      ,	__lowerCAmelCase   )


if __name__ == "__main__":
			print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]