code: def save_checkpoint(self, model_state, overwrite_most_recent=False):
      state = {}
      state.update(model_state)
      state.update(model_state[torchbearer.METRICS])
  
      string_state = {str(key): state[key] for key in state.keys()}
      filepath = self.fileformat.format(**string_state)
  
      if self.most_recent is not None and overwrite_most_recent:
          try:
              os.remove(self.most_recent)
          except OSError:
              warnings.warn(
                  "Failed to delete old file. Are you running two checkpointers with the same filename?"
              )
  
      if self.save_model_params_only:
          torch.save(
              model_state[torchbearer.MODEL].state_dict(),
              filepath,
              pickle_module=self.pickle_module,
              pickle_protocol=self.pickle_protocol,
          )
      else:
          torch.save(
              model_state[torchbearer.SELF].state_dict(),
              filepath,
              pickle_module=self.pickle_module,
              pickle_protocol=self.pickle_protocol,
          )
  
      self.most_recent = filepath
  
imports: import torchbearer
  import torch
  from torchbearer.callbacks.callbacks import Callback
  import os
  import warnings
  from torchbearer.bases import get_metric
label_desc: Use image node_id 2 for calling the _Checkpointer obj's underlying member method code with example usage: obj.save_checkpoint(model_state, overwrite_most_recent) without return types