Creating an getEnergy() Function

[galenoshea]

We are trying to calculate the energy from the hopfield network and are wondering if there is simple way to do this.

[HRamses]

Hi galenoshea!

So far there is no getEnergy() function planned. But if you look at our paper https://arxiv.org/pdf/2008.02217.pdf equation (2) should be fairly straightforward to implement.

[NickFleece]

Related to this, what's the best way to get the state pattern from the hopfield class? I'm having some trouble extracting it

[a-kore]

A little late but I think I managed to implement a get_energy function:

def get_energy(R, Y, beta):
    lse = -(1.0/beta)*torch.logsumexp(beta*(torch.bmm(R, Y.transpose(1,2))), dim=2) # -lse(beta, Y^T*R)
    lnN = (1.0/beta)*torch.log(torch.tensor(Y.shape[1], dtype=float)) # beta^-1*ln(N)
    RTR = 0.5*torch.bmm(R, R.transpose(1,2)) # R^T*R
    M = 0.5*((torch.max(torch.linalg.norm(Y, dim=2), dim=1))[0]**2.0) # 0.5*M^2  *very large value*
    energy = lse + lnN + RTR + M
    return energy

I published a short notebook with a similar pattern retrieval task for Simpson faces and it shows expected behavior where the energy is minimized for the retrieved pattern.

[bschaefl]

Closing issue. Seems to be resolved by @a-kore.