Added required as_cuda_ndarray_variable in conv_gemm optimizer

theano/sandbox/cuda/opt.py

@@ -1391,10 +1391,14 @@ def local_conv_gemm(node):
                     prod2 *= node.op.imshp[0]
                 # compare to decide
                 if prod1 > prod2:
-                    return [GpuCorrMM_gradWeights('valid', subsample, pad)(
+                    # (we need to wrap the result in as_cuda_ndarray_variable,
+                    # because we are not allowed to replace a CudaNdarray with
+                    # a DimShuffle instance in a graph optimization)
+                    return [theano.sandbox.cuda.as_cuda_ndarray_variable(
+                            GpuCorrMM_gradWeights('valid', subsample, pad)(
                             gpu_contiguous(img.dimshuffle(1, 0, 2, 3)),
                             gpu_contiguous(kern.dimshuffle(1, 0, 2, 3))
-                            ).dimshuffle(1, 0, 2, 3)]
+                            ).dimshuffle(1, 0, 2, 3))]
             # use GpuCorrMM if we did not choose GpuCorrMM_gradWeights above
             return [GpuCorrMM('valid', subsample, pad)(
                     gpu_contiguous(img), gpu_contiguous(kern))]