docstr: Warm up the model, while the architecture weights are not trained.
docstr_tok: ["Warm","up","the","model",",","while","the","architecture","weights","are","not","trained","."]
code: def _warm_up(self):
      """
      Warm up the model, while the architecture weights are not trained.
      """
      for epoch in range(self.epoch, self.start_epoch):
          self.logger.info(
              "\n--------Warmup epoch: %d--------\n", epoch + 1
          )
          self._train_epoch(epoch, self.model_optim)
          # adjust learning rate
          self.scheduler.step()
  
          # validation
          _, _ = self._validate()
          if epoch % 10 == 0:
              filename = os.path.join(
                  self.config.model_dir, "checkpoint_%s.pth" % epoch
              )
              self.save_checkpoint(epoch, filename)
  
file_path: nni/examples/nas/legacy/oneshot/pfld/lib/trainer.py
imports: from __future__ import absolute_import, division, print_function
  import os
  import time
  import torch
  import numpy
  from nni.algorithms.nas.pytorch.fbnet import FBNetTrainer
  from nni.nas.pytorch.utils import AverageMeter
  from .utils import accuracy
label_desc: Use image node_id 4 for calling the PFLDTrainer obj's underlying member method code with example usage: obj._warm_up() without return types