Use more inheritance

lm_eval/tasks/lambada_cloze.py

@@ -2,38 +2,11 @@ import json
 from lm_eval.base import Task, rf
 from lm_eval.metrics import mean, perplexity
 from lm_eval.utils import sh
+from lm_eval.tasks.lambada import LAMBADA
 from best_download import download_file
 
 
-class LAMBADA_cloze(Task):
-    def download(self):
-        sh("mkdir -p data/lambada")
-        download_file(
-            "http://eaidata.bmk.sh/data/lambada_test.jsonl", 
-            "data/lambada/lambada_test.jsonl", 
-            "4aa8d02cd17c719165fc8a7887fddd641f43fcafa4b1c806ca8abc31fabdb226"
-        )
-
-    def has_training_docs(self):
-        return False
-
-    def has_validation_docs(self):
-        return True
-
-    def has_test_docs(self):
-        return False
-
-    def training_docs(self):
-        pass
-
-    def validation_docs(self):
-        with open("data/lambada/lambada_test.jsonl") as fh:
-            for line in fh:
-                yield json.loads(line)
-
-    def test_docs(self):
-        pass
-
+class LAMBADA_cloze(LAMBADA):
     def doc_to_text(self, doc):
         return doc['text'].rsplit(' ', 1)[0] + " ____. ->"
 
@@ -42,28 +15,3 @@ class LAMBADA_cloze(Task):
     
     def fewshot_description(self):
         return "Fill in blank:\n"
-
-    def construct_requests(self, doc, ctx):
-        ll, is_greedy = rf.loglikelihood(ctx, self.doc_to_target(doc))
-
-        return ll, is_greedy
-    
-    def process_results(self, doc, results):
-        ll, is_greedy = results
-
-        return {
-            'ppl': ll,
-            'acc': int(is_greedy)
-        }
-        
-    def aggregation(self):
-        return {
-            'ppl': perplexity,
-            'acc': mean
-        }
-
-    def higher_is_better(self):
-        return {
-            'ppl': False,
-            'acc': True
-        }