code: def maybe_freeze_trunk_batchnorm(self):
      if self.freeze_trunk_batchnorm:
          self.models["trunk"].apply(
              c_f.set_layers_to_eval("BatchNorm")
          )
  
imports: import torch
  import tqdm
  from ..utils import common_functions
  from ..utils import loss_tracker
  from ..utils.key_checker import KeyChecker, KeyCheckerDict
label_desc: Use image node_id 22 for calling the BaseTrainer obj's underlying member method code with example usage: obj.maybe_freeze_trunk_batchnorm() without return types