class_docstr: Median Smoothing 2D.
  
  :param kernel_size: aperture linear size; must be odd and greater than 1.
  :param stride: stride of the convolution.
code: def __init__(self, kernel_size=3, stride=1):
      super(MedianSmoothing2D, self).__init__()
      self.kernel_size = kernel_size
      self.stride = stride
      padding = int(kernel_size) // 2
      if _is_even(kernel_size):
          # both ways of padding should be fine here
          # self.padding = (padding, 0, padding, 0)
          self.padding = (0, padding, 0, padding)
      else:
          self.padding = _quadruple(padding)
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.modules.utils import _quadruple
  from .base import Processor
label_desc: Use image node_id 1 to create a new MedianSmoothing2D object from inherited base classes: Processor with example: obj = MedianSmoothing2D(kernel_size, stride)