code: def load_checkpoint(self, checkpoint_dir):
      checkpoint_path = os.path.join(checkpoint_dir, "model.pth")
      self.model.load_state_dict(torch.load(checkpoint_path))
  
file_path: ray/python/ray/tune/examples/mnist_pytorch_trainable.py
imports: from __future__ import print_function
  import argparse
  import os
  import torch
  import torch.optim
  import ray
  from ray import train, tune
  from ray.tune.schedulers import ASHAScheduler
  from ray.tune.examples.mnist_pytorch import train_func, test_func, get_data_loaders, ConvNet
label_desc: Use image node_id 4 for calling the TrainMNIST obj's underlying member method code with example usage: obj.load_checkpoint(checkpoint_dir) without return types