Fix issue in local_subtensor_incsubtensor

theano/tensor/opt.py

@@ -1910,14 +1910,22 @@ def local_subtensor_inc_subtensor(node):
         if not x.owner.op.set_instead_of_inc:
             return
 
-        if x.owner.inputs[2:] == node.inputs[1:] and tuple(x.owner.op.idx_list) == tuple(node.op.idx_list):
-            # if x[idx] and y have the same ndim (and shape), directly return y
-            if x.owner.inputs[0].ndim - (len(node.op.idx_list) - sum([isinstance(idx, slice) for idx in node.op.idx_list])) == x.owner.inputs[1].ndim:
-                return [x.owner.inputs[1]]
-            # else y is broadcastable, return alloc of broadcastable y
+        if (x.owner.inputs[2:] == node.inputs[1:] and
+                tuple(x.owner.op.idx_list) == tuple(node.op.idx_list)):
+            out = node.outputs[0]
+            y = x.owner.inputs[1]
+            # If the dtypes differ, cast y into x.dtype
+            if x.dtype != y.dtype:
+                y = y.astype(x.dtype)
+            if out.type == y.type:
+                # if x[idx] and y have the same type, directly return y
+                return [y]
             else:
+                # The difference is related to broadcasting pattern
+                assert out.broadcastable != y.broadcastable
+                # We have to alloc y to the shape of x[idx]
                 x_subtensor = node.op(x.owner.inputs[0], *x.owner.inputs[2:])
-                return [T.alloc(x.owner.inputs[1], *x_subtensor.shape)]
+                return [T.alloc(y, *x_subtensor.shape)]
         else:
             return