onnx sub flavor

To save an exportONNXNetwork compatible Deep Learning Toolbox model, use mlflow.matlab.save_model or mlflow.matlab.log_model with the Network option:

% Save a network, specify the output location
mlflow.matlab.save_model(Network=net, Path="/work/models/mymodel")

Or to log a model:

% In order to log a model in a specific run in a specific experiment, first set an experiment
py.mlflow.set_experiment("My MATLAB Experiment")
% And start a run
py.mlflow.start_run()
% Then log the model, when logging a model, Path is not required
mlflow.matlab.log_model(Network=net)
% End the run
py.mlflow.end_run()

Again, it is possible to additionally specify MATLABFiles to include those in the model as well. Such that users who do have MATLAB and Deep Learning Toolbox installed and licensed can also load the original Deep Learning Toolbox network back into MATLAB and use it there.