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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)
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