return disconnected type instead of undefined

theano/scan_module/scan_op.py

@@ -1249,7 +1249,8 @@ class Scan(PureOp):
         return ipos + opos
 
     def connection_pattern(self, node):
-        connection_pattern = [[True for output in node.outputs]]
+        # The gradient wrt to n_steps is disconnected
+        connection_pattern = [[False for output in node.outputs]]
         connection_pattern += [[False for output in node.outputs]
                               for x in node.inputs[1:]]
 
@@ -1286,8 +1287,7 @@ class Scan(PureOp):
             else:
                 e = len(self.tap_array[0])
             p = iidx
-            if (node.inputs[iidx + 1] in self.outer_nitsot(node) or
-               node.inputs[iidx + 1] in self.outer_shared(node)):
+            if node.inputs[iidx + 1] in self.outer_nitsot(node)
                 return None
             if node.inputs[iidx + 1] in self.outer_non_seqs(node):
                 loc_idx = self.outer_non_seqs(node).index(
@@ -1298,8 +1298,10 @@ class Scan(PureOp):
                 s = e
                 if p < self.n_seqs:
                     e += 1
-                else:
+                elif p - self.n_seqs < len(self.tap_array):
                     e += len(self.tap_array[p - self.n_seqs])
+                else:
+                    e += 1
 
             return self.inputs[s:e]
         for oidx, out in enumerate(node.outputs):
@@ -1308,8 +1310,8 @@ class Scan(PureOp):
                 ils = _get_inner_inps(iidx)
 
                 if ils is None:
-                    # The gradient should be undefined, not disconnected
-                    connection_pattern[iidx + 1][oidx] = True
+                    # The gradient should be disconnected
+                    connection_pattern[iidx + 1][oidx] = False
                 else:
                     for inner_out in ols:
                         if hasattr(inner_out, 'dtype'):
@@ -1662,7 +1664,7 @@ class Scan(PureOp):
         if type(outputs) not in (list, tuple):
             outputs = [outputs]
         # Re-order the gradients correctly
-        gradients = [grad_undefined(self, 0, inputs[0], 'Number of steps')]
+        gradients = [DisconnectedType()()]
 
         offset = (self.n_mit_mot +
                   self.n_mit_sot +
@@ -1702,9 +1704,7 @@ class Scan(PureOp):
                     'Shared Variable with update')
                 for x in xrange(self.n_shared_outs)]
         start = len(gradients)
-        gradients += [
-                grad_undefined(self, x + start, inputs[x + start],
-                    'Dimension of memory buffer for output')
+        gradients += [DisconnectedType()()
                 for x in xrange(self.n_nit_sot)]
         begin = end