[to #42322933] Fix rouge metrics for chinese text

修复 TextGenerationMetric 中 Rouge 指标计算中文时结果不正确的问题

为文本生成添加 BLEU 指标
        Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10254323

modelscope/metrics/builder.py

@@ -18,6 +18,10 @@ class MetricKeys(object):
     SSIM = 'ssim'
     AVERAGE_LOSS = 'avg_loss'
     FScore = 'fscore'
+    BLEU_1 = 'bleu-1'
+    BLEU_4 = 'bleu-4'
+    ROUGE_1 = 'rouge-1'
+    ROUGE_L = 'rouge-l'
 
 
 task_default_metrics = {

modelscope/metrics/text_generation_metric.py

@@ -1,11 +1,14 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
 
-from typing import Dict
+from typing import Dict, Iterable, List
+
+from nltk.translate.bleu_score import sentence_bleu
+from rouge import Rouge
 
 from modelscope.metainfo import Metrics
+from modelscope.metrics.base import Metric
+from modelscope.metrics.builder import METRICS, MetricKeys
 from modelscope.utils.registry import default_group
-from .base import Metric
-from .builder import METRICS, MetricKeys
 
 
 @METRICS.register_module(
@@ -17,20 +20,49 @@ class TextGenerationMetric(Metric):
     """
 
     def __init__(self):
-        self.preds = []
-        self.tgts = []
-        from rouge_score import rouge_scorer
-        self.scorer = rouge_scorer.RougeScorer(['rougeL'], use_stemmer=True)
+        self.preds: List[str] = []
+        self.tgts: List[str] = []
+        self.rouge = Rouge()
+
+    @staticmethod
+    def is_chinese_char(char: str):
+        # the length of char must be 1
+        return '\u4e00' <= char <= '\u9fa5'
+
+    # add space for each chinese char
+    def rebuild_str(self, string: str):
+        return ' '.join(''.join([
+            f' {char} ' if self.is_chinese_char(char) else char
+            for char in string
+        ]).split())
 
-    def add(self, outputs: Dict, inputs: Dict):
+    def add(self, outputs: Dict[str, List[str]], inputs: Dict = None):
         ground_truths = outputs['tgts']
         eval_results = outputs['preds']
-        self.preds.extend(eval_results)
-        self.tgts.extend(ground_truths)
+        for truth in ground_truths:
+            self.tgts.append(self.rebuild_str(truth))
+        for result in eval_results:
+            self.preds.append(self.rebuild_str(result))
 
     def evaluate(self):
-        scores = [
-            self.scorer.score(pred, tgt)['rougeL'].fmeasure
-            for pred, tgt in zip(self.preds, self.tgts)
-        ]
-        return {MetricKeys.F1: sum(scores) / len(scores)}
+
+        def mean(iter: Iterable) -> float:
+            return sum(iter) / len(self.preds)
+
+        rouge_scores = self.rouge.get_scores(hyps=self.preds, refs=self.tgts)
+        rouge_1 = mean(map(lambda score: score['rouge-1']['f'], rouge_scores))
+        rouge_l = mean(map(lambda score: score['rouge-l']['f'], rouge_scores))
+        pred_split = tuple(pred.split(' ') for pred in self.preds)
+        tgt_split = tuple(tgt.split(' ') for tgt in self.tgts)
+        bleu_1 = mean(
+            sentence_bleu([tgt], pred, weights=(1, 0, 0, 0))
+            for pred, tgt in zip(pred_split, tgt_split))
+        bleu_4 = mean(
+            sentence_bleu([tgt], pred)
+            for pred, tgt in zip(pred_split, tgt_split))
+        return {
+            MetricKeys.ROUGE_1: rouge_1,
+            MetricKeys.ROUGE_L: rouge_l,
+            MetricKeys.BLEU_1: bleu_1,
+            MetricKeys.BLEU_4: bleu_4
+        }