adding unittest for CudaNdarrayType.filter with broadcasting

theano/sandbox/cuda/tests/test_var.py

@@ -75,6 +75,19 @@ class T_updates(unittest.TestCase):
                 updates=output_updates, givens=output_givens)
         output_func()
 
+    def test_3(self):
+        # Test that broadcastable dimensions don't screw up
+        # update expressions.
+        data = numpy.random.rand(10,10).astype('float32')
+        output_var = f32sc(name="output",
+                value=numpy.zeros((10,10), 'float32'))
+
+        # the update_var has type matrix, and the update expression
+        # is a broadcasted scalar, and that should be allowed.
+        output_func = theano.function(inputs=[], outputs=[],
+                updates={output_var:output_var.sum().dimshuffle('x', 'x')})
+        output_func()
+
 class T_ifelse(unittest.TestCase):
     def setUp(self):
         utt.seed_rng()

theano/sandbox/cuda/type.py

@@ -128,9 +128,15 @@ class CudaNdarrayType(Type):
         if (other.type.dtype != self.dtype):
             raise TypeError('Incompatible dtype', (self.dtype,
                                                    other.type.dtype))
-        if (other.type.broadcastable != self.broadcastable):
+        if any(bi and not obi
+                for obi, bi in zip(
+                    other.type.broadcastable,
+                    self.broadcastable)):
             raise TypeError('Incompatible broadcastable', (self.broadcastable,
                 other.type.broadcastable))
+        if other.type.broadcastable != self.broadcastable:
+            rebroadcast = tensor.Rebroadcast(*enumerate(self.broadcastable))
+            other = rebroadcast(other)
         return theano.sandbox.cuda.basic_ops.GpuFromHost()(other)
 
     @staticmethod