backward compatible

ud.py

@@ -14,17 +14,25 @@ class UniversalDependenciesPipeline(TokenClassificationPipeline):
       else:
         t.append((k,(s,e)))
     m=[(0,0)]+[j for i,j in t]+[(0,0)]
-    r=list(super().preprocess(sentence=" ".join(i for i,j in t)))
-    w=self.tokenizer.convert_ids_to_tokens(r[0]["input_ids"][0])
+    r=super().preprocess(sentence=" ".join(i for i,j in t))
+    try:
+      f=True
+      k=r["input_ids"]
+    except:
+      r=list(r)[0]
+      f=False
+    w=self.tokenizer.convert_ids_to_tokens(r["input_ids"][0])
     if len(m)!=len(w):
       for i,j in enumerate(w):
         if j.endswith("@@"):
           s,e=m[i]
           m.insert(i+1,(s+len(j)-2,e))
           m[i]=(s,s+len(j)-2)
-    r[0]["offset_mapping"]=torch.tensor([m]).to(self.device)
-    r[0]["sentence"]=sentence
-    return iter(r)
+    r["offset_mapping"]=torch.tensor([m]).to(self.device)
+    r["sentence"]=sentence
+    if f:
+      return r
+    return iter([r])
   def _forward(self,model_inputs):
     import torch
     v=model_inputs["input_ids"][0].tolist()