code: def __init__(self, in_channels, channels):
      inter_channels = in_channels // 4
      layers = [
          nn.Conv2d(
              in_channels, inter_channels, 3, padding=1, bias=False
          ),
          nn.BatchNorm2d(inter_channels),
          nn.ReLU(),
          nn.Dropout(0.1),
          nn.Conv2d(inter_channels, channels, 1),
      ]
  
      super(FCNHead, self).__init__(*layers)
  
file_path: deep-learning-for-image-processing/pytorch_segmentation/fcn/src/fcn_model.py
imports: from collections import OrderedDict
  from typing import Dict
  import torch
  from torch import nn, Tensor
  from torch.nn import functional
  from .backbone import resnet50, resnet101
label_desc: Use image node_id 1 to create a new FCNHead object from inherited base classes: nn with example: obj = FCNHead(in_channels, channels)