class_docstr: Average Smoothing 2D.
  
  :param channels: number of channels in the output.
  :param kernel_size: aperture size.
code: def __init__(self, channels, kernel_size):
      kernel = torch.ones((channels, 1, kernel_size, kernel_size)) / (
          kernel_size * kernel_size
      )
      super(AverageSmoothing2D, self).__init__(kernel)
  
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 AverageSmoothing2D object from inherited base classes: ConvSmoothing2D with example: obj = AverageSmoothing2D(channels, kernel_size)