fix to clone functionality of theano

theano/scan_module/scan_utils.py

@@ -169,14 +169,24 @@ def clone(output,
         shared variables still use the same underlying storage, so they
         will always have the same value.
     """
+    items = replace.items()
+    tmp_replace = [(x, x.type()) for x, y in items]
+    new_replace = [(x, y) for ((_, x), (_, y)) in zip(tmp_replace,
+                                                           items)]
+    _, _outs, _ = rebuild_collect_shared(output,
+                                         [],
+                                         tmp_replace,
+                                         [],
+                                         strict,
+                                         copy_inputs)
+
+    _, outs, _ = rebuild_collect_shared(_outs,
+                                        [],
+                                        new_replace,
+                                        [],
+                                        strict,
+                                        copy_inputs)
 
-    inps, outs, other_stuff = rebuild_collect_shared(output,
-                                                     [],
-                                                     replace,
-                                                     [],
-                                                     strict,
-                                                     copy_inputs
-                                                     )
     return outs
 
 

theano/scan_module/tests/test_scan.py

@@ -3427,6 +3427,23 @@ class T_Scan(unittest.TestCase):
         assert numpy.allclose(outs[2], v_w + 3)
         assert numpy.allclose(sh.get_value(), v_w + 4)
 
+    def test_clone(self):
+        def test(x, y, mention_y):
+            if mention_y:
+                d = 0.1 + 0 * y
+            else:
+                d = 0.1
+            out = theano.clone(y, replace={x:x + d})
+            theano.printing.debugprint(out)
+            return theano.function([], out)()
+
+        x = theano.shared(numpy.asarray(0., dtype=theano.config.floatX))
+        assert numpy.allclose(test(x, tensor.sum((x+1)**2), mention_y=False),
+                              1.21000003815)
+        assert numpy.allclose(test(x, tensor.sum((x+1)**2), mention_y=True),
+                              1.21000003815)
+
+
 def test_speed():
     #
     # This function prints out the speed of very simple recurrent