tau_q is multiplied instead of divison

[aakash-saboo]

Hi.
Thanks for your work @youngkyunJang !
I noticed that to implement equation 1 of the paper i.e to compute the quantization vector using Soft quantization, tau_q is multiplied instead of division.

def Soft_Quantization(X, C, N_books, tau_q):
    L_word = int(C.size()[1]/N_books)
    x = T.split(X, L_word, dim=1)
    c = T.split(C, L_word, dim=1)
    for i in range(N_books):
        soft_c = F.softmax(squared_distances(x[i], c[i]) * (-tau_q), dim=-1)
        if i==0:
            Z = soft_c @ c[i]
        else:
            Z = T.cat((Z, soft_c @ c[i]), dim=1)
    return Z

Please let me know if there is a correction.

Thanks
Aakash

[youngkyunJang]

Hello, Thanks for finding the error.

Actually, the paper is written wrong... what I meant was multiplying tau_q to increase the value of squared_distances.

I will update the paper version that fixes the error.

[aakash-saboo]

Thanks a lot for your quick response!