INNER CODE UNIT · Python

test_generator

vietnh1009/QuickDraw · train.py:59

    test_generator = DataLoader(test_set, **test_params)
    print("there are {} images for test phase".format(test_set.__len__()))


    model = QuickDraw(num_classes=training_set.num_classes)

    if os.path.isdir(opt.log_path):
        shutil.rmtree(opt.log_path)
    os.makedirs(opt.log_path)
    writer = SummaryWriter(opt.log_path)
    # writer.add_graph(model, torch.rand(opt.batch_size, 1, 28, 28))

    if torch.cuda.is_available():
        model.cuda()

    criterion = nn.CrossEntropyLoss()
    if opt.optimizer == "adam":
        optimizer = torch.optim.Adam(model.parameters(), lr=opt.lr)

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