code: def load_checkpoint(checkpoint_path):
      model_state_dict = torch.load(checkpoint_path)
      return model_state_dict
  
file_path: nni/examples/trials/mnist-pbt-tuner-pytorch/mnist.py
imports: import argparse
  import logging
  import os
  import nni
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torchvision import datasets, transforms
label_desc: Use image node_id 4 for calling a global function with example usage: load_checkpoint(checkpoint_path) and returns: model_state_dict