Ground truth values

[UTpH]

Hi!
So the paper defines the ground truth similarity score as np.exp(-normalized_ged) which you calculate as the target in simgnn.py.
But in score() you call calculate_normalized_ged() of utils.py that does not take the exponent of GED.
Why is that? Shouldn't calculate_normalized_ged() be soemthing like this:-

def calculate_normalized_ged(prediction, target):
    normalized_ged = data["ged"]/(0.5*(len(data["labels_1"])+len(data["labels_2"])))
    norm_ged = np.exp(-normalized_ged)
    return norm_ged

[BehroozMansouri]

That is somehow my question too.
In the score, the prediction, is the transformed ged prediction. How can I get the original ged estimation?

Is this correct:

real_ged_prediction = (-np.log(prediction.data.item())*(0.5 * (len_label1 + len_label2)))