from summ_eval.bert_score_metric import BertScoreMetric
from evaluation.summeval_metric import SummEvalMetric
from typing import List, Dict


class BertScore(SummEvalMetric):
    metric_name = "bert score"
    range = (0, 1)
    higher_is_better = True
    requires_heavy_compute = True

    def __init__(self):
        se_metric = BertScoreMetric()
        super(BertScore, self).__init__(se_metric)

    def evaluate(
        self, inputs: List[str], targets: List[str], keys: List[str] = ["bert_score_f1"]
    ) -> Dict[str, float]:
        # TODO zhangir: update when datasets api is merged
        return super(BertScore, self).evaluate(inputs, targets, keys)