get_cost_grads_svm.py

def get_cost_grads(self, X, w, y):
    distances = self.distances(w)

    # Get current cost
    L = 1 / 2 * np.dot(w, w) - self.C * np.sum(distances)

    dw = np.zeros(len(w))

    for ind, d in enumerate(distances):
        if d == 0:  # if sample is not on the support vector
            di = w  # (alpha * y[ind] * X[ind]) = 0
        else:
            # (alpha * y[ind] * X[ind]) = y[ind] * X[ind]
            di = w - (self.C * y[ind] * X[ind])
        dw += di
    return L, dw / len(X)