code: def add_dropout(
      model: smp.Unet,
      decoder_channels: List[int] = (256, 128, 64, 32, 16),
      classes=1,
      activation=None,
  ):
      seg_head = SegmentationHead(
          in_channels=decoder_channels[-1],
          out_channels=classes,
          activation=activation,
          kernel_size=3,
      )
      model.add_module("segmentation_head", seg_head)
      model.initialize()
  
file_path: baal/experiments/segmentation/utils.py
imports: from typing import List
  import numpy
  import segmentation_models_pytorch
  from segmentation_models_pytorch.base.modules import Activation
  import torch
  from torch import nn
  from torch.nn import functional
  from torchvision import datasets
  from torchvision.transforms import transforms
  from baal import ActiveLearningDataset
label_desc: Use image node_id 2 for calling a global function with example usage: add_dropout(model, decoder_channels, classes, activation) without return types