Hi, I’d like to ask a basic question about custom layers for Tensorflow UFF model. Let’s say a network has a part not supported by TensorRT, and I am going to replace the part with a custom layer.
To my understanding, when using custom layers for Caffe,
Caffe is supposed to give you a “model file” and “deploy.txt”, and you can manually touch the model definition (i.e., deploy.txt) so that it includes proper custom layer definitions, and you can provide the custom layers’ implementation with C++ API.
However, I am not sure how this can work with Tensorflow.
Tensorflow conversion requires “Tensorflow model -> frozen binary .pb graph -> binary-ish UFF format”. In this procedure, intermediate files are all binary. How can I manually modify the part and replace?