code: import torch
  import torch.nn as nn
  import torch.optim as optim
  import argparse
  import numpy as np
  import torch
  import os
  import sys
  
  sys.path.append(os.getcwd())
  
  from packnet_sfm.models.SelfSupModel import SelfSupModel
  
  model = SelfSupModel()
  
  PATH = '/home/ai/work/data/experiments/default_config-train_kitti-2022.03.14-09h57m43s/epoch=49_KITTI_raw-eigen_val_files-velodyne-abs_rel_pp_gt=0.089.ckpt'
  
   # model = Net()
  # optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)
  
  checkpoint = torch.load(PATH)
  print(checkpoint)
  print(type(checkpoint))
  # model.load_state_dict(checkpoint['model_state_dict'])
  # optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
  epoch = checkpoint['epoch']
  # loss = checkpoint['loss']
  
  model.eval()
  output = model()
  # print(epoch,loss)
  #
  # model.eval()
  # # - or -
  # model.train()
  
apis: torch.load