376b01c2e338ec63e638f62a76d67f6a9323e47c,code/deep/DeepCoral/DeepCoral.py,,,#,109

Before Change

    model = load_pretrain(model)
    for epoch in range(1, epochs + 1):
        train(epoch, model)
        t_correct = test(model)
        if t_correct > correct:
            correct = t_correct
        print("source: {} to target: {} max correct: {} max accuracy{: .2f}%\n".format(
              source_name, target_name, correct, 100. * correct / len_target_dataset ))

After Change

    source_loader, target_train_loader, target_test_loader = load_data(source_name, target_name, CFG["data_path"])

    model = models.DeepCoral(CFG["n_class"], CFG["backbone"]).to(DEVICE)
    optimizer = torch.optim.SGD([
        {"params": model.sharedNet.parameters()},
        {"params": model.fc.parameters()},
        {"params": model.cls_fc.parameters(), "lr": 10 * CFG["lr"]},
    ], lr=CFG["lr"], momentum=CFG["momentum"], weight_decay=CFG["l2_decay"])

    train(source_loader, target_train_loader, target_test_loader, model, optimizer, CFG)

Instances