Fix import problem with OutputGuard.

theano/compile/mode.py

@@ -100,9 +100,14 @@ def register_optimizer(name, opt):
         raise ValueError('Optimizer name already taken: %s' % name)
     predefined_optimizers[name] = opt
 
+def register_OutputGuard_c_code(type):
+    OutputGuard.c_code_types.append(type)
+
 class OutputGuard(gof.Op):
     destroy_map = {0:[0]}
     view_map = {0:[0]}
+    c_code_types = []
+
     def make_node(self, x):
         return gof.Apply(self, [x], [x.type()])
     def __eq__(self, other):
@@ -124,12 +129,7 @@ class OutputGuard(gof.Op):
             return """
             %(z)s = %(x)s;
             """ % locals()
-        elif (isinstance(node.inputs[0].type,
-                (theano.tensor.TensorType,
-                    theano.sandbox.cuda.CudaNdarrayType,
-                    theano.tensor.raw_random.RandomStateType)) or
-                node.inputs[0].type.__class__.__name__ == 'SparseType'
-                ):
+        elif (isinstance(node.inputs[0].type, tuple(self.c_code_types))):
             # These are Python object types
             return """
             Py_XDECREF(%(z)s);

theano/sandbox/cuda/type.py

@@ -351,6 +351,12 @@ class CudaNdarrayType(Type):
             ret.append('-use_fast_math')
         return ret
 
+
+# Register CudaNdarrayType to the OutputGuard list of know type
+# to have OutputGuard generate c code for this type
+theano.compile.mode.register_OutputGuard_c_code(CudaNdarrayType)
+
+
 # THIS WORKS
 # But CudaNdarray instances don't compare equal to one another, and what about __hash__ ?
 # So the unpickled version doesn't equal the pickled version, and the cmodule cache is not

theano/sparse/basic.py

@@ -326,6 +326,11 @@ class SparseType(gof.Type):
     def is_valid_value(self, a):
         return scipy.sparse.issparse(a) and (a.format == self.format)
 
+# Register CudaNdarrayType to the OutputGuard list of know type
+# to have OutputGuard generate c code for this type
+theano.compile.mode.register_OutputGuard_c_code(SparseType)
+
+
 # for more dtypes, call SparseType(format, dtype)
 def matrix(format, name=None, dtype=None):
     if dtype is None:

theano/tensor/basic.py

@@ -910,6 +910,10 @@ class TensorType(Type):
         else:
             return ()
 
+# Register CudaNdarrayType to the OutputGuard list of know type
+# to have OutputGuard generate c code for this type
+theano.compile.mode.register_OutputGuard_c_code(TensorType)
+
 # Easy constructors
 
 def tensor(*args, **kwargs):

theano/tensor/raw_random.py

@@ -53,6 +53,10 @@ class RandomStateType(gof.Type):
                 return False
         return True
 
+# Register CudaNdarrayType to the OutputGuard list of know type
+# to have OutputGuard generate c code for this type
+theano.compile.mode.register_OutputGuard_c_code(RandomStateType)
+
 random_state_type = RandomStateType()