code: def load_checkpoint(checkpoint_path, net, optimizer):
      checkpoint_params = torch.load(
          os.path.join(checkpoint_path, "params.pth")
      )
      net.load_state_dict(checkpoint_params["state_dict"])
      optimizer.load_state_dict(checkpoint_params["optimizer"])
      with open(
          os.path.join(checkpoint_path, "monitor_metrics.pickle"), "rb"
      ) as handle:
          monitor_metrics = pickle.load(handle)
      starting_epoch = checkpoint_params["epoch"] + 1
      return starting_epoch, monitor_metrics
  
imports: import numpy
  import logging
  import subprocess
  import os
  import torch
  from collections import OrderedDict
  import plotting
  import sys
  import importlib.util
  import pandas
  import pickle
label_desc: Use image node_id 4 for calling a global function with example usage: load_checkpoint(checkpoint_path, net, optimizer) and returns: starting_epoch,  monitor_metrics