program: do not prepare_train if no training data

pasp/program.py

@@ -149,7 +149,7 @@ def __init__(self, net, data: Data, learnable: bool, rep: str, nvals: int, opt_p
     # Derivatives of the logic program to be passed to backwards.
     self.dw = None
     # Initialize dw so we can use inference without learning.
-    self.prepare_train(0)
+    if self.data[0].train is not None: self.prepare_train(0)
 
     # Temp: accuracy
     # import torchvision