code: def __init__(self, in_channels: int, num_classes: int) -> None:
      super(DeepLabHead, self).__init__(
          ASPP(in_channels, [12, 24, 36]),
          nn.Conv2d(256, 256, 3, padding=1, bias=False),
          nn.BatchNorm2d(256),
          nn.ReLU(),
          nn.Conv2d(256, num_classes, 1),
      )
  
imports: from collections import OrderedDict
  from typing import Dict, List
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from .resnet_backbone import resnet50, resnet101
  from .mobilenet_backbone import mobilenet_v3_large
label_desc: Use image node_id 1 to create a new DeepLabHead object from inherited base classes: nn with example: obj = DeepLabHead(in_channels, num_classes)