






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		:       Dict			     = {
           "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		:       Union[str, Any]			     = {
           "linear": PIL.Image.LINEAR,
           "bilinear": PIL.Image.BILINEAR,
           "bicubic": PIL.Image.BICUBIC,
           "lanczos": PIL.Image.LANCZOS,
           "nearest": PIL.Image.NEAREST,
       }






def 				lowerCamelCase__      (    __lowerCamelCase			:     Dict		):
  __UpperCAmelCase							:	Any           =  (images / 2 + 0.5).clamp(0  ,		1		)
  __UpperCAmelCase							:	Union[str, Any]           =  images.cpu().permute(0  ,		2  ,		3  ,		1		).float().numpy()
  __UpperCAmelCase							:	List[Any]           =  numpy_to_pil(__lowerCamelCase		)
  return images







def 				lowerCamelCase__      (    __lowerCamelCase			:     Optional[int]		):
  if images.ndim == 3:
    __UpperCAmelCase							:	Tuple           =  images[None, ...]
  __UpperCAmelCase							:	Optional[Any]           =  (images * 255).round().astype("""uint8"""		)
  if images.shape[-1] == 1:
    # special case for grayscale (single channel) images
    __UpperCAmelCase							:	Tuple           =  [Image.fromarray(image.squeeze()  ,		mode="""L"""		) for image in images]
  else:
    __UpperCAmelCase							:	Any           =  [Image.fromarray(__lowerCamelCase		) for image in images]

  return pil_images










from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

a		:       Dict			     = typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
a		:       Any			     = typing.Union[np.floataa, int, float]  # noqa: UP007






def 				lowerCamelCase__      (    __lowerCamelCase			:     Vector  ,		__lowerCamelCase			:     Vector		):
  return np.sqrt(np.sum((np.asarray(__lowerCamelCase		) - np.asarray(__lowerCamelCase		)) ** 2		)		)






def 				lowerCamelCase__      (    __lowerCamelCase			:     Vector  ,		__lowerCamelCase			:     Vector		):
  return sum((va - va) ** 2 for va, va in zip(__lowerCamelCase  ,		__lowerCamelCase		)		) ** (1 / 2)


if __name__ == "__main__":






       def 				lowerCamelCase__      (    ):
         from timeit import timeit

         print("""Without Numpy"""		)
         print(
             timeit(
                 """euclidean_distance_no_np([1, 2, 3], [4, 5, 6])"""  ,		number=10000  ,		globals=globals()  ,		)		)
         print("""With Numpy"""		)
         print(
             timeit(
                 """euclidean_distance([1, 2, 3], [4, 5, 6])"""  ,		number=10000  ,		globals=globals()  ,		)		)







       benchmark()


