[WIP] Feature multilayer perceptron

[EvertBunschoten]

Proposed Changes

Addition of multi-layer perceptron class which can be used to evaluate trained multi-layer perceptrons in processes such as thermodynamic state evaluation in data-driven fluid models.

Related Work

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[pcarruscag]

Do you want to introduce this first as a standalone library, and then start using it for fluid models?

[EvertBunschoten]

@pcarruscag Yes I want to introduce the multilayer perceptron as an option for users and developers for things like data-driven fluid models. Do you think it would be good to add a template CFluidModel child class demonstrating how the MLP class can be used to create data-driven fluid models (apart from writing a tutorial of course)?

[pcarruscag]

Sounds good. Initially it would be enough to have some unit tests that would already show how to setup the network, together with documentation / example of the file format. Applications can come after.

Some initial comments: Please move the files to toolboxes/ and ideally use a namespace for the new classes. Start the class names with C as we do, e.g. CIOMap.

Then, how large are the models you've used so far? and how important is performance to this feature? (Just so I know how much to comment on that)

[EvertBunschoten]

Of course I'll provide an example of an MLP input file, as well as a python script I wrote that translates an MLP trained through TensorFlow to such an input file.

Very well, I'll move the files from the numerics folder to the common folder and change names accordingly.

The models I used so far had between 5 and 50 perceptrons and up to 15 layers. Performance is quite important, as evaluation of MLP's is generally more computationally expensive than for example lookup tables. The larger the MLP architecture, the more costly evaluations get of course. Any improvement to the computation speed will therefore be welcome. In terms of memory, the MLP's don't seem to be an issue so far.

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This pull request introduces 3 alerts when merging 47b456cb3d65ce3f29a6521e947caec819eb8335 into 88c8392ff1028af640a8b0bc90304367ea45ded3 - view on LGTM.com

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[EvertBunschoten]

Hi Pedro, thanks for your reply. I don't know how to safely typedef the mlpdouble type the way you suggested. I thought you meant that I just had to copy the way su2double was defined in code_config.hpp, but I guess that's not right. Do you know an example showing how this works?

[pcarruscag]

in your type config file do:

#ifdef MLP_CUSTOM_TYPE
using mlpdouble = MLP_CUSTOM_TYPE;
#else
using mlpdouble = double;
#endif

in SU2 before the first MLP include do:

#define MLP_CUSTOM_TYPE su2double
#include ...

[EvertBunschoten]

Thanks Pedro!

[bigfooted]

@EvertBunschoten I suggest to first finish and close this one before moving on to the hydrogen flamelets PR

[EvertBunschoten]

I'll ignore the request for review the same way you ignored my questions shrug

Could you clarify your questions? I sent you a message on Slack.