Dear Cañas, Jhovanny,
Would you mind chopping everything after training/RMSprop/Variable_7 off ? Or everything after dense_4/kernel off ? If these happen toward the end of the model, maybe it's OK. The technique I'm suggesting is called Model Cutting . You can add --output "dense_4/kernel" or --output "training/RMSprop/Variable_7" to your mo_tf.py command which creates a new exit point for the model. This may be OK if these occur toward the end of the model and there's nothing important (such as an output layer) afterward.
Please let me know the answer on this forum. The exception coming from Model Optimizer is clear :
Graph contains 0 node after executing <class 'extensions.front.input_cut.InputCut'>. It considered as error because resulting IR will be empty which is not usual
There is a sub-graph in your model which contains zero nodes. Maybe chopping it off will solve the problem.