e3883e98057396d886f90328ea32e0f0a01f2535,examples/tetris.py,,main,#,133

Before Change

        cnn_test_accs.append(acc)

    print("avg test acc SE3: {}".format(np.mean(se3_test_accs)))
    print("avg test acc CNN: {}".format(np.mean(cnn_test_accs)))
    N_classes = len(testset[1])
    print("random guessing accuracy: {}".format(1 / N_classes))
    // c=correct, r0=initial rotation

After Change

    N_test = 100
    trainset = get_volumes(rotate=True)  // train with randomly rotated pieces but only once

    network = SE3Net().cuda()
    train(network, trainset, N_epochs=N_epochs)
    se3_test_accs = []
    for _ in range(N_test):
        testset = get_volumes(rotate=True)

Instances