TensorFlow Conversion Custom Layers Possible?

Hi. I am converting my tensorflow model over to TensorRT with the UFF tool.

I successful generate a UFF file albeit with some expected warnings that layers are unsupported:

Warning: No conversion function registered for layer: AddN yet.
Converting as custom op AddN l_4/AddN
name: "l_4/AddN"
op: "AddN"
input: "l_4/Conv/Elu"
input: "l_4/Conv_7/Elu"
attr {
  key: "N"
  value {
    i: 2
  }
}
attr {
  key: "T"
  value {
    type: DT_FLOAT
  }
}

When I try to load the UFF file into the UFF parser though it crashes saying unsupported layer!

[ERROR] UFFParser: Validator error: l_15/AddN: Unsupported operation _AddN
ASSERT(parser->parse(uffFile.c_str(), network, nvinfer::DataType::kFLOAT)) failed at ros/src/tensorrt/EngineBuilder.cpp:118
Backtrace: 
main in ??:0
__libc_start_main in /build/eglibc-SvCtMH/eglibc-2.19/csu/libc-start.c:321
_start in ??:0

The caffe parser has a “setPluginFactory” method which is called when an unrecognized layer exists however there seems to be no such option with the UFF parser. Is there another way to provide plugins for UFF/TensorFlow? This would be greatly disappointing if there was no way to use plugins in conjunction with Tensorflow.

class ICaffeParser
{
public:
 virtual void setPluginFactory(IPluginFactory* factory)
};

Apparently not supported “yet” https://devtalk.nvidia.com/default/topic/1025899/?comment=5227975