Matlab does not currently support Generative Adversarial Neural Networks

Thank you for your suggestion. I have already tried that. Actually the problem is we cannot embed such layers into a matlab DAG. a very simple sample code:

% from MaxconNet

   net = dagnn.DagNN();
  conv1Block = dagnn.ConvTranspose('size',[5 5 256 100],'hasBias',true,'upsample',[1,1],'crop',[0,0,0,0]);
  net.addLayer('G_conv1',conv1Block,{'data_rand'},{'G1'},{'G1f','G1b'});
  net.addLayer('G_bn1',dagnn.BatchNorm(),{'G1'},{'G1bn'},{'Gbn1f','Gbn1b','Gbn1c'});
  net.addLayer('Grelu1',GreluBlock,{'G1bn'},{'G1x'});

% from Matlab

      subdag1 = layerGraph([ ...
      convolution2dLayer([1 1],64,'NumChannels',192,'Name','inception_3a-1x1')
      reluLayer('Name','inception_3a-relu_1x1')]);

% create layer pool

   someLayers=[
     subdag1.Layers
     net];

%%%%%%%%%%%%% Error

Error using nnet.cnn.layer.Layer/vertcat
Cannot convert from 'dagnn.DagNN' to 'nnet.cnn.layer.Layer'.

If we update the above code with :

someLayers=[
 subdag1.Layers
 net.layers];

Error using nnet.cnn.layer.Layer/vertcat
Cannot convert from 'struct' to 'nnet.cnn.layer.Layer'.

I have no idea how to correct such errors.

Please ignore the logic behind this example since it is just for studding possibility