code: def load(model, optimiser):
      if os.path.exists(CHECKPOINT_NAME):
          checkpoint = torch.load(CHECKPOINT_NAME)
          model.load_state_dict(checkpoint["model_state_dict"])
          optimiser.load_state_dict(checkpoint["optimizer_state_dict"])
          grad_step = checkpoint["grad_step"]
          # print(f'Restored checkpoint from {CHECKPOINT_NAME}.')
          return grad_step
      return 0
  
imports: import numpy
  import pandas
  from numpy import matrix
  from scipy import linalg
  from matplotlib.pylab import rcParams
label_desc: Use image node_id 4 for calling a global function with example usage: load(model, optimiser) and returns: int, grad_step