fix to allow more gpu sum to be done on the gpu.

theano/sandbox/cuda/opt.py

@@ -259,7 +259,11 @@ def local_gpu_sum(node):
                     if hasattr(new_gsum, 'c_code_reduce_%s'%pattern):
                         reshaped_x = x.reshape(tensor.stack(*new_in_shp))
                         sum_reshaped_x = host_from_gpu(new_gsum(gpu_from_host(reshaped_x)))
-                        unreshaped_sum = sum_reshaped_x.reshape(tensor.stack(*shape_of[node.outputs[0]]))
+
+                        if sum_reshaped_x.ndim != node.outputs[0].ndim:
+                            unreshaped_sum = sum_reshaped_x.reshape(tensor.stack(*shape_of[node.outputs[0]]))
+                        else:
+                            unreshaped_sum = sum_reshaped_x
                         if unreshaped_sum.type == node.outputs[0].type:
                             return [unreshaped_sum]
                         else:

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -36,6 +36,14 @@ def tes_use():
 def test_sum():
     """
     test sum pattern 1, 11, 10, 01, 100, 110, 011, 001, 111, 0011, 0101, 0111, 1011, 1111
+
+    test sum pattern implemented with reshape:
+    1000, 0100, 0010, 0001, 11111
+
+    others implemented by reshape that are not tested
+    0011,0101,0110,1001,1010,1100
+    1110,1101,1011
+    
     TODO: test with broadcast
     """
     for shape, pattern in [((100,3,1300),[1]),
@@ -66,6 +74,15 @@ def test_sum():
                            ((4100,4,3,2),[0,2,3]),((4,4100,3,2),[0,2,3]),((4,3,4100,2),[0,2,3]),#((4,3,2,4100),[0,2,3]),#1011
                            ((4100,4,3,2),[1,2,3]),((4,4100,3,2),[1,2,3]),((4,3,4100,2),[1,2,3]),((4,3,2,4100),[1,2,3]),#0111
                            ((4100,2,3,4),[0,1,2,3]),((2,4100,3,4),[0,1,2,3]),((2,3,4100,4),[0,1,2,3]),((2,3,4,4100),[0,1,2,3]),#1111
+
+
+                           #test pattern implemented by reshape
+                           ((4100,4,3,2),[0]),((4,4100,3,2),[0]),((4,3,4100,2),[0]),((4,3,2,4100),[0]),#1000
+                           ((4100,4,3,2),[1]),((4,4100,3,2),[1]),((4,3,4100,2),[1]),((4,3,2,4100),[1]),#0100
+                           ((4100,4,3,2),[2]),((4,4100,3,2),[2]),((4,3,4100,2),[2]),((4,3,2,4100),[2]),#0010
+                           ((4100,4,3,2),[3]),((4,4100,3,2),[3]),((4,3,4100,2),[3]),((4,3,2,4100),[3]),#0001
+                           ((1100,2,3,4,5),[0,1,2,3,4]),((2,1100,3,4,5),[0,1,2,3,4]),((2,3,1100,4,5),[0,1,2,3,4]),((2,3,4,1100,5),[0,1,2,3,4]),((2,3,4,5,1100),[0,1,2,3,4]),#11111
+
                            ]:
         a = tensor.TensorType('float32',(False,)*len(shape))()
         b = T.Sum(pattern)(a)