code: def create_DLR_V3_pretrained(num_classes=1, **kwargs):
      """
      Creates a pretrained version of the DeepLab Resnet model but substitutes num_classes for output instead of default 21.
      :param num_classes:
      :return:
      """
      model = DeepLabv3_plus(
          num_classes=21,
          pretrained=True,
          os=8,
          nInputChannels=3,
          print=True,
          **kwargs,
      )
      last_linear = nn.Sequential(
          nn.Conv2d(
              304, 256, kernel_size=3, stride=1, padding=1, bias=False
          ),
          nn.BatchNorm2d(256),
          nn.ReLU(),
          nn.Conv2d(
              256, 256, kernel_size=3, stride=1, padding=1, bias=False
          ),
          nn.BatchNorm2d(256),
          nn.ReLU(),
          nn.Conv2d(256, num_classes, kernel_size=1, stride=1),
      )
      model.last_linear = last_linear
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.model_zoo
label_desc: Use image node_id 4 for calling a global function with example usage: create_DLR_V3_pretrained(num_classes) without return types