def extract_scores()

in align/train.py [0:0]

• 23 lines of code
• 4 McCabe index (conditional complexity)

def extract_scores(batch, criss_features, aligner, info, configs):
    coocc, semi_matched_coocc, matched_coocc, freq_src, freq_trg = info
    all_scores = list()
    for i in range(0, len(batch), configs.batch_size):
        subbatch = batch[i:i+configs.batch_size]
        src_words, trg_words = zip(*subbatch)
        features = torch.tensor(
            [
                [
                    matched_coocc[x[0]][x[1]],
                    semi_matched_coocc[x[0]][x[1]],
                    coocc[x[0]][x[1]],
                    freq_src[x[0]],
                    freq_trg[x[1]]
                ] for x in subbatch
            ]
        ).float().to(configs.device).reshape(-1, 5)
        if configs.use_criss:
            subbatch_crissfeat = torch.cat(criss_features[i:i+configs.batch_size], dim=0)
            features = torch.cat((subbatch_crissfeat, features), dim=-1).detach()
        scores = aligner(features).squeeze(-1)
        all_scores.append(scores)
    return torch.cat(all_scores, dim=0)