def decode_candidates()

in drqa/reader/model.py [0:0]

• 33 lines of code
• 10 McCabe index (conditional complexity)

    def decode_candidates(score_s, score_e, candidates, top_n=1, max_len=None):
        """Take argmax of constrained score_s * score_e. Except only consider
        spans that are in the candidates list.
        """
        pred_s = []
        pred_e = []
        pred_score = []
        for i in range(score_s.size(0)):
            # Extract original tokens stored with candidates
            tokens = candidates[i]['input']
            cands = candidates[i]['cands']

            if not cands:
                # try getting from globals? (multiprocessing in pipeline mode)
                from ..pipeline.drqa import PROCESS_CANDS
                cands = PROCESS_CANDS
            if not cands:
                raise RuntimeError('No candidates given.')

            # Score all valid candidates found in text.
            # Brute force get all ngrams and compare against the candidate list.
            max_len = max_len or len(tokens)
            scores, s_idx, e_idx = [], [], []
            for s, e in tokens.ngrams(n=max_len, as_strings=False):
                span = tokens.slice(s, e).untokenize()
                if span in cands or span.lower() in cands:
                    # Match! Record its score.
                    scores.append(score_s[i][s] * score_e[i][e - 1])
                    s_idx.append(s)
                    e_idx.append(e - 1)

            if len(scores) == 0:
                # No candidates present
                pred_s.append([])
                pred_e.append([])
                pred_score.append([])
            else:
                # Rank found candidates
                scores = np.array(scores)
                s_idx = np.array(s_idx)
                e_idx = np.array(e_idx)

                idx_sort = np.argsort(-scores)[0:top_n]
                pred_s.append(s_idx[idx_sort])
                pred_e.append(e_idx[idx_sort])
                pred_score.append(scores[idx_sort])
        return pred_s, pred_e, pred_score