code: def load_checkpoint(self, tmp_checkpoint_dir):
      checkpoint_path = os.path.join(tmp_checkpoint_dir, "model.pth")
      self.model.load_state_dict(torch.load(checkpoint_path))
  
imports: import os
  import torch
  from torch import nn
  from ray import train, tune
  import random
  import os
  import tempfile
  from ray import train, tune
  from ray.train import Checkpoint
label_desc: Use image node_id 4 for calling the MyTrainableClass obj's underlying member method code with example usage: obj.load_checkpoint(tmp_checkpoint_dir) without return types