def _compute()

in metrics/meteor/meteor.py [0:0]

• 39 lines of code
• 12 McCabe index (conditional complexity)

    def _compute(self, predictions, references, alpha=0.9, beta=3, gamma=0.5):
        multiple_refs = isinstance(references[0], list)
        if NLTK_VERSION >= version.Version("3.6.5"):
            # the version of METEOR in NLTK version 3.6.5 and earlier expect tokenized inputs
            if multiple_refs:
                scores = [
                    meteor_score.meteor_score(
                        [word_tokenize(ref) for ref in refs],
                        word_tokenize(pred),
                        alpha=alpha,
                        beta=beta,
                        gamma=gamma,
                    )
                    for refs, pred in zip(references, predictions)
                ]
            else:
                scores = [
                    meteor_score.single_meteor_score(
                        word_tokenize(ref), word_tokenize(pred), alpha=alpha, beta=beta, gamma=gamma
                    )
                    for ref, pred in zip(references, predictions)
                ]
        else:
            if multiple_refs:
                scores = [
                    meteor_score.meteor_score(
                        [[word_tokenize(ref) for ref in group] for group in references][0],
                        word_tokenize(pred),
                        alpha=alpha,
                        beta=beta,
                        gamma=gamma,
                    )
                    for ref, pred in zip(references, predictions)
                ]
            else:
                scores = [
                    meteor_score.single_meteor_score(ref, pred, alpha=alpha, beta=beta, gamma=gamma)
                    for ref, pred in zip(references, predictions)
                ]

        return {"meteor": np.mean(scores)}