Shape missmatching

[miha-skalic]

Following the tutorial i do following:

mu_chembl, cov_chembl = pickle.load(open("chembl_50k_stats.p", 'rb')).values()
gen_mol_act = get_predictions(gen_mol)

In this case mu_chembl is array of shape (512, 512), and gen_mol_act is of shape (4640, 512)

now, calling
calculate_frechet_distance(mu1=np.mean(gen_mol_act, axis=0), mu2=mu_chembl, sigma1=np.cov(gen_mol_act.T), sigma2=cov_chembl) yields an assertion error: Training and test mean vectors have different lengths

Essentially, mu1 is of shape (512, ) while mu2 is of shape (512, 512).

What would be the correct way of solving this?

[miha-skalic]

Problem resolved. I had a bug in loading the data.

mu_chembl is (correctly) of shape (512, ).