谁能帮我看看这个报错是什么意思哇？

Question

遇到报错AssertionError

Successfully loaded first 20 categories for training and last 20 for testing!
Traceback (most recent call last):
  File "D:\d.py", line 1438, in _exec
    pydev_imports.execfile(file, globals, locals)  # execute the script
  File "D:\e.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "E:/t.py", line 349, in <module>
    main()
  File "E:/t.py", line 298, in main
    _init_(args)
  File "E:/t.py", line 339, in _init_
    assert os.path.isfile(args.pretrained1)
AssertionError

部分代码

def _init_(args):
    if not os.path.exists('checkpoints'):
        os.makedirs('checkpoints')
    if not os.path.exists('checkpoints/' + args.exp_name):
        os.makedirs('checkpoints/' + args.exp_name)
    if not os.path.exists('checkpoints/' + args.exp_name + '/' + 'models'):
        os.makedirs('checkpoints/' + args.exp_name + '/' + 'models')
    trainset = RegistrationData(ModelNet40Data(train=True, num_points=args.num_points, unseen=args.unseen),
                                partial_source=args.partial_source, noise=args.noise, outliers=args.outliers)
    testset = RegistrationData(ModelNet40Data(train=False, num_points=args.num_points, unseen=args.unseen),
                                partial_source=args.partial_source, noise=args.noise, outliers=args.outliers)
    train_loader = DataLoader(trainset, batch_size=args.batch_size, shuffle=True, drop_last=True, num_workers=args.workers)
    test_loader = DataLoader(testset, batch_size=args.test_batch_size, shuffle=False, drop_last=False, num_workers=args.workers)

    if not torch.cuda.is_available():
        args.device = 'cpu'
    args.device = torch.device(args.device)

    model = tpccNet()
    model = model.to(args.device)

    ptnet = PointNet(emb_dims=args.emb_dims)
    model2 = itmpeNet(feature_model=ptnet)
    model2 = model2.to(args.device)

    checkpoint = None
    if args.resume:
        assert os.path.isfile(args.resume)
        checkpoint = torch.load(args.resume)
        args.start_epoch = checkpoint['epoch']        #Here checkpoint is used to call the saved model to continue training

        model2.load_state_dict(checkpoint['model2'])

    if args.pretrained1:
        assert os.path.isfile(args.pretrained1)     #这里报错
        model.load_state_dict(torch.load(args.pretrained1, map_location='cpu'))
    model.to(args.device)

    if args.eval:
        test(args, model, model2, test_loader, textio)
    else:
        train(args, model, model2, train_loader, test_loader, boardio, textio, checkpoint)

Answer 1

这是断言错误抛出的异常。断言那一行，期望args.pretrained1是一个文件，期望落空了，因此抛出异常。如果没有这一行，估计下一行会出错，因为args.pretrained1不是一个文件，torch.load也无法正常执行。