



'''simple docstring'''


from __future__ import annotations






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     a_									=sorted(lowercase__							)
     a_									=len(lowercase__							)
     a_									=length >> 1
     return (
         (sorted_list[mid_index] + sorted_list[mid_index - 1]) / 2
         if length % 2 == 0
         else sorted_list[mid_index]
     )






def 			UpperCAmelCase_							(		):


     '''simple docstring'''







     import doctest

     doctest.testmod()


if __name__ == "__main__":
  main()







'''simple docstring'''


import unittest
from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image

from diffusers.utils.outputs import BaseOutput







@dataclass
class 						UpperCAmelCase						(		__a):


 '''simple docstring'''




 __magic_name__       :			Union[List[PIL.Image.Image], np.ndarray]







class 						UpperCAmelCase						(		unittest.TestCase):


 '''simple docstring'''




 def    lowercase_	( self)			->   List[str]:



      """simple docstring"""







      a_									=CustomOutput(images=np.random.rand(1				,	3				,	4				,	4))

      # check every way of getting the attribute
      assert isinstance(outputs.images				,	np.ndarray)
      assert outputs.images.shape == (1, 3, 4, 4)
      assert isinstance(outputs["images"]				,	np.ndarray)
      assert outputs["images"].shape == (1, 3, 4, 4)
      assert isinstance(outputs[0]				,	np.ndarray)
      assert outputs[0].shape == (1, 3, 4, 4)

      # test with a non-tensor attribute
      a_									=CustomOutput(images=[PIL.Image.new("RGB"				,	(4, 4))])

      # check every way of getting the attribute
      assert isinstance(outputs.images				,	lowerCAmelCase_)
      assert isinstance(outputs.images[0]				,	PIL.Image.Image)
      assert isinstance(outputs["images"]				,	lowerCAmelCase_)
      assert isinstance(outputs["images"][0]				,	PIL.Image.Image)
      assert isinstance(outputs[0]				,	lowerCAmelCase_)
      assert isinstance(outputs[0][0]				,	PIL.Image.Image)




 def    lowercase_	( self)			->   Optional[int]:



      """simple docstring"""







      a_									=CustomOutput({"images": np.random.rand(1				,	3				,	4				,	4)})

      # check every way of getting the attribute
      assert isinstance(outputs.images				,	np.ndarray)
      assert outputs.images.shape == (1, 3, 4, 4)
      assert isinstance(outputs["images"]				,	np.ndarray)
      assert outputs["images"].shape == (1, 3, 4, 4)
      assert isinstance(outputs[0]				,	np.ndarray)
      assert outputs[0].shape == (1, 3, 4, 4)

      # test with a non-tensor attribute
      a_									=CustomOutput({"images": [PIL.Image.new("RGB"				,	(4, 4))]})

      # check every way of getting the attribute
      assert isinstance(outputs.images				,	lowerCAmelCase_)
      assert isinstance(outputs.images[0]				,	PIL.Image.Image)
      assert isinstance(outputs["images"]				,	lowerCAmelCase_)
      assert isinstance(outputs["images"][0]				,	PIL.Image.Image)
      assert isinstance(outputs[0]				,	lowerCAmelCase_)
      assert isinstance(outputs[0][0]				,	PIL.Image.Image)


