code: def __init__(self, in_channels, out_channels, dilation):
      modules = [
          nn.Conv2d(
              in_channels,
              out_channels,
              3,
              padding=dilation,
              dilation=dilation,
              bias=False,
          ),
          nn.BatchNorm2d(out_channels),
          nn.ReLU(),
      ]
      super(ASPPConv, self).__init__(*modules)
  
file_path: serve/examples/image_segmenter/deeplabv3/deeplabv3.py
imports: import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new ASPPConv object from inherited base classes: nn with example: obj = ASPPConv(in_channels, out_channels, dilation)