fix for the grad method

theano/scan_module/scan_op.py

@@ -1198,6 +1198,37 @@ class Scan(PureOp):
                          for o, x in izip(node.outputs, scan_outs)]
         return scan_outs
 
+    def get_input_pos(self, output_index):
+        ipos = 0
+        opos = output_index
+        for otaps, itaps in zip(self.mitmot_out_taps(), self.mitmot_taps()):
+            if len(otaps) > opos:
+                return ipos
+            else:
+                opos = opos - len(otaps)
+                ipos += len(itaps)
+        for dx, taps in enumerate(self.mitsot_taps()):
+            if opos == 0:
+                return ipos
+            else:
+                opos = opos - 1
+                ipos += len(taps)
+        if opos < self.info['n_sit_sot']:
+            return ipos + opos
+        else:
+            return -1
+
+    def get_output_slice_idx(self, output_index):
+        ipos = 0
+        opos = output_index
+        for otaps in zip(self.mitmot_out_taps()):
+            if len(otaps) > 0:
+                return ipos
+            else:
+                opos = opos - 1
+                ipos += len(otaps)
+        return ipos + opos
+
     ### GRAD FUNCTION
     def grad(self, args, g_outs):
 
@@ -1303,12 +1334,12 @@ class Scan(PureOp):
 
         # 7.3. compute gradients of the inputs given one output
         for dx, out in enumerate(clean_outputs):
-            if g_outs[dx] != None:
-                inner_g_out = safe_new(g_outs[dx][0])
+            input_pos = self.get_input_pos(dx)
+            if input_pos >= 0:
+                corresponding_input = self_inputs[input_pos]
+                tmp = tensor.grad(out.sum(), corresponding_input)
+                inner_g_out = safe_new(tmp)
             else:
-                # We do not have a gradient on this output so we need a
-                # placeholder, which for now has the same dtype as the
-                # output
                 inner_g_out = safe_new(out)
             ###
             #### I need to clip the gradient HERE !!
@@ -1356,7 +1387,9 @@ class Scan(PureOp):
                     # this try is for catching non ndarray inputs (random
                     # states) it is more of a safety check ( all random
                     # states should be after n_outs_not_shared ...
-                    g_outs[i] = tensor.zeros_like(scan_outputs[i])
+                    g_outs[i] = tensor.cast(
+                        tensor.zeros_like(scan_outputs[i]),
+                        inner_gfn_outs[self.get_output_slice_idx(i)].dtype)
                 except Exception:
                     g_outs[i] = theano.tensor.constant(
                         numpy.array(0, theano.config.floatX))