merged

theano/gradient.py

@@ -132,14 +132,3 @@ def unimplemented_grad(op, x_pos, x):
     """
     msg = '%s.grad not implemented for input %i'%(op, x_pos)
     return Raise(msg=msg)(x)
-
-
-class GradientUndefined(Exception): pass
-
-def undefined_grad(op, x_pos, x):
-    msg = "Undefined gradient - do not use in computations"
-    exc = RuntimeError
-    return Raise(msg=msg, exc=exc)(x)
-
-def grad(self, inputs, out_storage):
-    return [g_x0, undefined_grad(self, 1, inputs[1])]

theano/sandbox/cuda/basic_ops.py

@@ -374,7 +374,7 @@ class GpuDimShuffle(Op):
         return sio.getvalue()
 
     def c_code_cache_version(self):
-        return (3,0)
+        return (1,0)
 
 class GpuSum(Op):
     """GpuSum is a Reduction along some dimensions by summation.

theano/sandbox/cuda/cuda_ndarray.cuh

@@ -334,13 +334,17 @@ int CudaNdarray_set_nd(CudaNdarray * self, const int nd)
         if (nd == -1) return 0;
 
         self->host_structure = (int*)malloc(cnda_structure_size(nd)*sizeof(int));
-        //initialize all dimensions and strides to 0
-        for (int i = 0; i < cnda_structure_size(nd); ++i) self->host_structure[i] = 0;
         if (NULL == self->host_structure)
         {
             PyErr_SetString(PyExc_MemoryError, "Failed to allocate dim or str");
             return -1;
         }
+        //initialize all dimensions and strides to 0
+        for (int i = 0; i < cnda_structure_size(nd); ++i)
+        {
+            self->host_structure[i] = 0;
+        }
+
         int struct_size = cnda_structure_size(nd);
         if (struct_size)
         {