Update xor-tydi.py

xor-tydi.py

@@ -108,39 +108,49 @@ class XORTyDi(datasets.GeneratorBasedBuilder):
         return splits
     
     def _generate_examples(self, files):
-        """Yields examples."""
-        # def process_train_entry(data):
-        #     if data.get('negative_passages') is None:
-        #         data['negative_passages'] = []
-        #     if data.get('positive_passages') is None:
-        #         data['positive_passages'] = []
-        #     if data.get('answers') is None:
-        #         data['answers'] = []
-        #     return data['query_id'], data
+        assert len(files) == 1
+        filepath = files[0]
 
+
+        def process_doc_text(doc):
+            if isinstance(doc["text"], list):
+                assert len(doc["text"]) == 1
+                return doc['text'][0].strip()
+            else:
+                assert isinstance(doc["text"], str)
+                return doc['text'].strip()
+
+        
+        # prepare doc
+        doc2docid = {}
+        with open(filepath, encoding="utf-8") as f:
+            all_data = json.load(f)
+            for i, data in enumerate(all_data):
+                positive_ctxs = data["positive_ctxs"]
+                hard_negative_ctxs = data["hard_negative_ctxs"]
+                ctxs = positive_ctxs + hard_negative_ctxs
+
+                for doc for ctxs:
+                    text = process_doc_text[doc]
+                    if text not in doc2docid:
+                        doc2docid[text] = len(doc2docid)
+                
         def process_train_entry(data, _id):
             positive_ctxs = data["positive_ctxs"]
             hard_negative_ctxs = data["hard_negative_ctxs"]
             # each ctx: {'title':... , 'text': ....}
 
             def process_ctx(ctxs, tag):
-                # assert len(doc["text"]) == 1
-                for doc in ctxs:
-                    if isinstance(doc["text"], list):
-                        assert len(doc["text"]) == 1
-                    else:
-                        assert isinstance(doc["text"], str)
-
+                text = process_doc_text(doc)
                 return [
                     {
                         "title": doc["title"],
-                        "text": doc["text"][0] if isinstance(doc["text"], list) else doc["text"],
-                        'docid': f'{tag}-{i}-{random.randint(*RANGE)}'
+                        "text": 
+                        # 'docid': f'{tag}-{i}-{random.randint(*RANGE)}'
+                        'docid': doc2docid[docid]
                     } for i, doc in enumerate(ctxs)
                 ]
 
-            _id = f"{_id}-{random.randint(*RANGE)}"
-            # import pdb; pdb.set_trace()
             return _id, {
                 "query_id": _id,
                 "query": data["question"],
@@ -160,8 +170,7 @@ class XORTyDi(datasets.GeneratorBasedBuilder):
                 "negative_passages": [],
             }
 
-        assert len(files) == 1
-        filepath = files[0]
+
         try:
             with open(filepath, encoding="utf-8") as f:
                 all_data = json.load(f)