Add a test for GpuCAReduce

theano/sandbox/gpuarray/tests/test_elemwise.py

 import unittest
 
-from theano import scalar
+from theano import scalar, gof
 from theano.gof import FunctionGraph
 from theano.gof.python25 import all, any
+from theano.tests.unittest_tools import SkipTest
 
-from theano.tensor.tests.test_elemwise import test_Broadcast, test_DimShuffle
+from theano.tensor.tests.test_elemwise import (test_Broadcast, test_DimShuffle,
+                                               test_CAReduce)
 
 from theano.sandbox.gpuarray.tests.test_basic_ops import rand_gpuarray
-from theano.sandbox.gpuarray.elemwise import GpuElemwise, GpuDimShuffle
+from theano.sandbox.gpuarray.elemwise import (GpuElemwise, GpuDimShuffle,
+                                              GpuCAReduce)
 from theano.sandbox.gpuarray.type import GpuArrayType
 
 from pygpu.array import gpuarray
@@ -30,3 +33,26 @@ class test_gpu_Broadcast(test_Broadcast):
 
 class test_GpuDimShuffle(test_DimShuffle):
     op = GpuDimShuffle
+
+class test_GpuCAReduce(test_CAReduce):
+    dtypes = ["float32"]
+    op = GpuCAReduce
+    reds = [scalar.add, scalar.mul]
+
+    def test_perform(self):
+        for dtype in self.dtypes + self.bin_dtypes:
+            for op in self.reds:
+                self.with_linker(gof.PerformLinker(), op, dtype=dtype)
+
+    def test_perform_nan(self):
+        raise SkipTest("for now")
+        for dtype in self.dtypes:
+            for op in self.reds:
+                self.with_linker(gof.PerformLinker(), op, dtype=dtype,
+                                 test_nan=True)
+
+    def test_c(self):
+        raise SkipTest("no C code")
+
+    def test_c_nan(self):
+        raise SkipTest("no C code")

theano/tensor/tests/test_elemwise.py

@@ -283,6 +283,7 @@ class test_Broadcast(unittest.TestCase):
 
 
 class test_CAReduce(unittest_tools.InferShapeTester):
+    op = CAReduce
 
     def with_linker(self, linker, scalar_op=scalar.add, dtype="floatX",
                     test_nan=False, tensor_op=None):
@@ -305,7 +306,7 @@ class test_CAReduce(unittest_tools.InferShapeTester):
                 dtype = theano.config.floatX
             x = TensorType(dtype, [(entry == 1) for entry in xsh])('x')
             if tensor_op is None:
-                e = CAReduce(scalar_op, axis=tosum)(x)
+                e = self.op(scalar_op, axis=tosum)(x)
             else:
                 e = tensor_op(x, axis=tosum)