f0fe1d57b54b7670ad4586e19d4383db561e84e7,code/distance/mmd.py,,linear_mmd2,#,17

Before Change

def linear_mmd2(f_of_X, f_of_Y):
    loss = 0.0
    delta = f_of_X - f_of_Y
    loss = torch.mean((delta[:-1] * delta[1:]).sum(1))
    return loss


// Consider linear time MMD with a polynomial kernel:

After Change

// f_of_Y: batch_size * k
def linear_mmd2(f_of_X, f_of_Y):
    loss = 0.0
    delta = f_of_X.float().mean() - f_of_Y.float().mean()
    loss = delta.dot(delta.T)
    return loss


// Consider linear time MMD with a polynomial kernel:

Instances