Merge dnn conv desc correctly.

theano/sandbox/cuda/dnn.py

@@ -231,6 +231,9 @@ class GpuDnnConvDesc(GpuOp):
     def c_compiler(self):
         return NVCC_compiler
 
+    def do_constant_folding(self, node):
+        return False
+
     def __init__(self, border_mode, subsample=(1, 1), conv_mode='conv'):
         if isinstance(border_mode, int):
             border_mode = (border_mode, border_mode)

theano/sandbox/cuda/tests/test_dnn.py

@@ -42,13 +42,30 @@ def test_dnn_conv_desc_merge():
     # CDataType is not DeepCopyable so this will crash if we don't use
     # borrow=True
     f = theano.function([], [theano.Out(desc1, borrow=True),
-                             theano.Out(desc2, borrow=True)])
+                             theano.Out(desc2, borrow=True)],
+                        mode=mode_with_gpu)
 
     d1, d2 = f()
 
     # This will be the case if they are merged, which would be bad.
     assert d1 != d2
 
+    desc1v2 = dnn.GpuDnnConvDesc(border_mode='valid', subsample=(2, 2),
+                                 conv_mode='conv')(img_shp, kern_shp)
+    f = theano.function([], [theano.Out(desc1, borrow=True),
+                             theano.Out(desc1v2, borrow=True)],
+                        mode=mode_with_gpu)
+    assert len(f.maker.fgraph.apply_nodes)
+    theano.printing.debugprint(f)
+
+    # CDATA type don't equal even if they represent the same object
+    # So we can't use debugmode with it.
+    if theano.config.mode not in ["DebugMode", "DEBUG_MODE"]:
+        d1, d2 = f()
+
+        # This will be the case if they are merged, which would be bad.
+        assert d1 == d2
+
 
 def test_dnn_conv_merge():
     """This test that we merge correctly multiple dnn_conv.