code: def load_weights(
      model: nn.Module, ckpt_path: str, verbose: bool = False
  ) -> None:
      if verbose:
          print_info(f"Load checkpoint from path: {ckpt_path}")
      current_state_dict = model.state_dict()
      new_state_dict = torch.load(ckpt_path, map_location="cpu")
      current_state_dict.update(new_state_dict)
      model.load_state_dict(current_state_dict)
  
imports: import torch
  from torch import nn
  from cftool.misc import print_info
label_desc: Use image node_id 1 for calling a global function with example usage: load_weights(model, ckpt_path, verbose) without return types