from .Qnn import Qnn

class QSVM(Qnn):
    def __init__(self, data, labels=None, test_size=0.2, random_state=None):
        super(QSVM, self).__init__(data, labels, test_size, random_state)
        self.result.update({
            "pca_2d": None,
            "pca_3d": None
        })
    
    def forward(self, x):
        # Implement SVM forward pass
        pass

    def train_model(self, epochs):
        # Implement SVM training logic
        pass

    def hinge_loss(self, output, target):
        # Implement hinge loss
        pass