added bleu score

belar/metrics/simple.py

@@ -3,14 +3,42 @@
 from Levenshtein import distance, ratio
 import typing as t
 from dataclasses import dataclass
-
+from nltk.tokenize import word_tokenize
+from nltk.translate.bleu_score import sentence_bleu
 from rouge_score import rouge_scorer
 
 from belar.metrics.base import Metric
 
 ROUGE_TYPES = t.Literal["rouge1", "rouge2", "rougeL"]
 
 
+@dataclass
+class BLEU(Metric):
+    weights: t.List[float] = [0.25, 0.25, 0.25, 0.25]
+    smoothing_function = None
+
+    @property
+    def name(self):
+        return "BLEU"
+
+    @property
+    def is_batchable(self):
+        return True
+
+    def score(self, ground_truth: t.List[str], generated_text: t.List[str]):
+        ground_truth_ = [[word_tokenize(text)] for text in ground_truth]
+        generated_text_ = [word_tokenize(text) for text in generated_text]
+        return [
+            sentence_bleu(
+                s1,
+                s2,
+                weights=self.weights,
+                smoothing_function=self.smoothing_function,
+            )
+            for s1, s2 in zip(ground_truth_, generated_text_)
+        ]
+
+
 @dataclass
 class ROUGE(Metric):
     type: t.Literal[ROUGE_TYPES]
@@ -21,11 +49,9 @@ def __post_init__(self):
             [self.type], use_stemmer=self.use_stemmer
         )
 
-    @property
     def name(self):
         return self.type
 
-    @property
     def is_batchable(self):
         return False