
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"):
			_A						      =				{
			    """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:
			_A						      =				{
			    """linear""": PIL.Image.LINEAR,
			    """bilinear""": PIL.Image.BILINEAR,
			    """bicubic""": PIL.Image.BICUBIC,
			    """lanczos""": PIL.Image.LANCZOS,
			    """nearest""": PIL.Image.NEAREST,
			}



def 		lowercase_    (     A__	)							->							Union[str, Any]:
				"""simple docstring"""

				snake_case				  =      (images / 2 + 0.5).clamp(0				,	1	)
				snake_case				  =      images.cpu().permute(0				,	2				,	3				,	1	).float().numpy()
				snake_case				  =      numpy_to_pil(A__	)
				return images





def 		lowercase_    (     A__	)							->							List[str]:
				"""simple docstring"""

				if images.ndim == 3:
								snake_case				  =      images[None, ...]
				snake_case				  =      (images * 255).round().astype("uint8"	)
				if images.shape[-1] == 1:
								# special case for grayscale (single channel) images
								snake_case				  =      [Image.fromarray(image.squeeze()				,	mode="L"	) for image in images]
				else:
								snake_case				  =      [Image.fromarray(A__	) for image in images]

				return pil_images



def 		lowercase_    (     A__				,	A__	)							->							List[Any]:
    """simple docstring"""

    snake_case				  =      [0 for i in range(r + 1	)]
    # nc0 = 1
    snake_case				  =      1
    for i in range(1				,	n + 1	):
        # to compute current row from previous row.
        snake_case				  =      min(A__				,	A__	)
        while j > 0:
            c[j] += c[j - 1]
            j -= 1
    return c[r]





print(binomial_coefficient(n=10, r=5))

