code: def load_model(model, path):
      print("⛄️ Reloading model from", path)
      model.load_state_dict(
          torch.load(path)
          if args.cuda
          else torch.load(
              path, map_location=lambda storage, loc: storage
          )
      )
  
imports: import os
  import time
  import argparse
  import socket
  from datetime import datetime
  import numpy
  import torch
  import torch.nn
  from torch.autograd import Variable
  from torch.optim import RMSprop
  from torch.utils.data import DataLoader
  from tensorboardX import SummaryWriter
  from neuralcoref.train.model import Model
  from neuralcoref.train.dataset import NCDataset, NCBatchSampler, load_embeddings_from_file, padder_collate, SIZE_PAIR_IN, SIZE_SINGLE_IN
  from neuralcoref.train.utils import SIZE_EMBEDDING
  from neuralcoref.train.evaluator import ConllEvaluator
label_desc: Use image node_id 6 for calling a global function with example usage: load_model(model, path) without return types