dcc5890dc2773090ab46a5e8bdd981a1104d9273,bindsnet/evaluation/__init__.py,,update_ngram_scores,#Any#Any#Any#Any#Any#,191

Before Change

            fire_order += ordering

        // Add counts for every n-gram
        for i in range(1, n+1):
            for beg in range(len(fire_order)-i+1):
                // For every ordering based on n (i)
                if tuple(fire_order[beg : beg+i]) not in ngram_scores:
                    ngram_scores[tuple(fire_order[beg : beg+i])] = torch.zeros(n_labels)
                ngram_scores[tuple(fire_order[beg : beg+i])][int(gold_labels[n_ex])] += 1

    return ngram_scores

After Change

        // Aggregate all of the firing neurons" indices
        for t in range(activity.size()[0]):
            ordering = torch.nonzero(activity[t].view(-1))
            if ordering.numel() > 0:
                ordering = ordering[:, 0].tolist()
                fire_order += ordering

Instances