Importing A Neural Network From Mathematica For Use In R

I am experimenting with platform interoperability between Mathematica and R.

My aim is to create an untrained Neural Network using Mathematica, export this network in MXNet format as a .json file, and import this network into R for a classification problem.

Creating the Network in Mathematica

Here i have created a basic neural network – this network is untrained. I have exported the network alongside the network parameters.

In mathematica the code is as follows.

dec=NetDecoder["Class",{"Chronic Kidney Disease","No Kidney Disease"}]  net =   NetInitialize@   NetChain[{BatchNormalizationLayer[], LinearLayer[20], Ramp,      DropoutLayer[0.1], LinearLayer[2], SoftmaxLayer[]},    "Input" -> 24, "Output" -> dec    ] 

There are 24 feature variables for the input and the output is the netdecoder. I then export this network.

Export["net.json", net, "MXNet"] 

This produces two files, one with the network, and another with the parameters. By using FilePrint we can visualise this

FilePrint["net.json"] 

which returns

{     "nodes":[         {"op":"null","name":"Input","inputs":[]},         {"op":"null","name":"1.Scaling","inputs":[]},         {"op":"null","name":"1.Biases","inputs":[]},         {"op":"null","name":"1.MovingMean","inputs":[]},         {"op":"null","name":"1.MovingVariance","inputs":[]},         {"op":"BatchNorm","name":"1","attrs":{"eps":"0.001","momentum":"0.9","fix_gamma":"false","use_global_stats":"false","axis":"1","cudnn_off":"0"},"inputs":[[0,0,0],[1,0,0],[2,0,0],[3,0,0],[4,0,0]]},         {"op":"null","name":"2.Weights","inputs":[]},         {"op":"null","name":"2.Biases","inputs":[]},         {"op":"FullyConnected","name":"2","attrs":{"num_hidden":"20","no_bias":"False"},"inputs":[[5,0,0],[6,0,0],[7,0,0]]},         {"op":"relu","name":"3$  0","inputs":[[8,0,0]]},         {"op":"Dropout","name":"4$  0","attrs":{"p":"0.1","mode":"always","axes":"()"},"inputs":[[9,0,0]]},         {"op":"null","name":"5.Weights","inputs":[]},         {"op":"null","name":"5.Biases","inputs":[]},         {"op":"FullyConnected","name":"5","attrs":{"num_hidden":"2","no_bias":"False"},"inputs":[[10,0,0],[11,0,0],[12,0,0]]},         {"op":"softmax","name":"6$  0","attrs":{"axis":"1"},"inputs":[[13,0,0]]},         {"op":"identity","name":"Output","inputs":[[14,0,0]]}     ],     "arg_nodes":[0,1,2,3,4,6,7,11,12],     "heads":[[15,0,0]],     "attrs":{         "mxnet_version":["int",10400]     } } 

Importing the Network into R

Now we have an untrained network as a .json file in MXNet format.

We can import this using:

library(rjson) mydata <- fromJSON(file="net.json")  

The Problem

Im not sure how to process the exported net in R. Is it possible to use the imported untrained network from Mathematica, to then be used in R to train on some data?