make sure the input var are of the right type.

theano/sandbox/gpuarray/conv.py

@@ -5,6 +5,7 @@ import theano
 from theano import config, gof
 from theano.sandbox.cuda.nvcc_compiler import NVCC_compiler
 from theano.sandbox.gpuarray.type import GpuArrayType
+from theano.sandbox.gpuarray.basic_ops import as_gpuarray_variable
 
 
 class GpuConv(gof.Op):
@@ -126,7 +127,8 @@ class GpuConv(gof.Op):
             raise TypeError('img must be 4D tensor')
         if kern.type.ndim != 4:
             raise TypeError('kern must be 4D tensor')
-
+        img = as_gpuarray_variable(img)
+        kern = as_gpuarray_variable(kern)
         broadcastable = [img.type.broadcastable[0], kern.type.broadcastable[0],
                          False, False]
         out = GpuArrayType(img.dtype, broadcastable)()
@@ -195,8 +197,8 @@ class GpuConv(gof.Op):
         # these files
         files = ['conv_kernel.cu', 'conv_full_kernel.cu', 'conv.cu']
         codes = ["CUdeviceptr (*cuda_get_ptr_raw)(gpudata *g);",
-                 "float* cuda_get_ptr(PyGpuArrayObject * o){return (float*) cuda_get_ptr_raw(o->ga.data);}",
-                 "const float* cuda_get_ptr(const PyGpuArrayObject * o){return (float*) cuda_get_ptr_raw(o->ga.data);}"]
+                 "float* cuda_get_ptr(PyGpuArrayObject * o){return (float*) (cuda_get_ptr_raw(o->ga.data) + o->ga.offset);}",
+                 "const float* cuda_get_ptr(const PyGpuArrayObject * o){return (float*) (cuda_get_ptr_raw(o->ga.data) + o->ga.offset);}"]
         codes += [open(os.path.join(os.path.split(__file__)[0], f)).read()
                   for f in files]
         return reduce(str.__add__, codes)