code: 
  
  
  
  
  
  
  """simple docstring"""
  
  
  
  
  
  
  def 						_UpperCamelCase			(  A    ,       A    ,       A			):
  			UpperCamelCase_     =index
  			UpperCamelCase_     =2 * index + 1
  			UpperCamelCase_     =2 * index + 2
  			if left_index < heap_size and unsorted[left_index] > unsorted[largest]:
  						UpperCamelCase_     =left_index
  
  			if right_index < heap_size and unsorted[right_index] > unsorted[largest]:
  						UpperCamelCase_     =right_index
  
  			if largest != index:
  						UpperCamelCase_    ,							UpperCamelCase_     =unsorted[index], unsorted[largest]
  						heapify(A    ,       A    ,       A			)
  
  
  
  
  def 						_UpperCamelCase			(  A			):
  			UpperCamelCase_     =len(A			)
  			for i in range(n // 2 - 1    ,       -1    ,       -1			):
  						heapify(A    ,       A    ,       A			)
  			for i in range(n - 1    ,       0    ,       -1			):
  						UpperCamelCase_    ,							UpperCamelCase_     =unsorted[i], unsorted[0]
  						heapify(A    ,       0    ,       A			)
  			return unsorted
  
  
  if __name__ == "__main__":
  				A_			  =    input("Enter numbers separated by a comma:\n").strip()
  				A_			  =    [int(item) for item in user_input.split(",")]
  				print(heap_sort(unsorted))
  
style_context: 
  
  
  
  
  
  
  """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 						__lowerCAmelCase   (			UpperCAmelCase       ):
  
  
  
  
  
  
  
    '''simple docstring'''
  
  
    __lowerCamelCase       :    Union[List[PIL.Image.Image], np.ndarray]
  
  
  
  
  class 						__lowerCAmelCase   (			unittest.TestCase       ):
  
  
  
  
  
  
  
    '''simple docstring'''
  
  
    def 					UpperCamelCase__   (      self:		Tuple					):
       UpperCamelCase_     =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
       UpperCamelCase_     =CustomOutput(images=[PIL.Image.new("RGB"				,			(4, 4)					)]					)
  
       # check every way of getting the attribute
       assert isinstance(outputs.images				,			UpperCamelCase_					)
       assert isinstance(outputs.images[0]				,			PIL.Image.Image					)
       assert isinstance(outputs["images"]				,			UpperCamelCase_					)
       assert isinstance(outputs["images"][0]				,			PIL.Image.Image					)
       assert isinstance(outputs[0]				,			UpperCamelCase_					)
       assert isinstance(outputs[0][0]				,			PIL.Image.Image					)
  
  
  
  
  
    def 					UpperCamelCase__   (      self:		Optional[int]					):
       # test output reinitialization with a `dict` for compatibility with `accelerate`
       UpperCamelCase_     =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
       UpperCamelCase_     =CustomOutput({"images": [PIL.Image.new("RGB"				,			(4, 4)					)]}					)
  
       # check every way of getting the attribute
       assert isinstance(outputs.images				,			UpperCamelCase_					)
       assert isinstance(outputs.images[0]				,			PIL.Image.Image					)
       assert isinstance(outputs["images"]				,			UpperCamelCase_					)
       assert isinstance(outputs["images"][0]				,			PIL.Image.Image					)
       assert isinstance(outputs[0]				,			UpperCamelCase_					)
       assert isinstance(outputs[0][0]				,			PIL.Image.Image					)
  