code: def encoder_layers(self) -> List[nn.Module]:
      return [
          self.stem,
          self.layer1,
          self.layer2,
          self.layer3,
          self.layer4,
      ]
  
imports: from collections import OrderedDict
  from typing import List, Union
  import torch
  from torch import nn
  from pytorch_toolbelt.modules import ACT_RELU, instantiate_activation_block, ChannelSpatialGate2d
  from pytorch_toolbelt.modules.encoders import EncoderModule, make_n_channel_input
label_desc: Use image node_id 2 for calling the XResNet obj's underlying member method code with example usage: obj.encoder_layers() and returns: list