return just the scores

nextus_regressor_class.py

@@ -30,8 +30,8 @@ class NextUsRegressor(nn.Module):
         # TODO: actually handle list of strings
         vals = regressed.flatten().tolist()
         # must return the whole thing, not just the 0-th element
-        strs = list()
-        for t, v in list(zip(txts, vals)):
-            strs.append(str(round(v, 4)) + "\t" + t[:100])
-        return "\n".join(strs)
+        # strs = list()
+        # for t, v in list(zip(txts, vals)):
+        #    strs.append(str(round(v, 4)) + "\t" + t[:100])
+        return "\n".join([str(round(s, 4)) for s in vals])
         # return torch.tensor(val).unsqueeze(1)