ML keras #4172
ML keras #4172
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This does not add a dependency on a third party library, so then I assume it instead embeds Keras in some way? Or have I misunderstood the purpose of this PR? |
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Is there a reason this is added to opm-common instead of being a separate repository? Do we, somehow, need to make (selected) objects in this repository, or any of its downstream repositories for that matter, "aware" of Keras? |
We use Keras for the training process (it doesnt need to be done in OPM). The generated models are subsequently embedded and run in OPM. I have updated the description to provide some context. |
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jenkins build this please |
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jenkins build this please |
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Maybe I'm missing something, but as far as I can tell no-one have answered my question from last week
I would really like an answer to this before I consider the details of the PR. |
Sorry for not answering earlier. The idea is to apply the ML-Keras inside OPM for different tasks. This is only the first PR to add the Keras ML model. The applications will follow. For an example of a ML near well model using ML-Keras check out https://github.com/cssr-tools/ML_near_well. Since the ML-Keras model framework is general. We hope it would be useful for the OPM community and therefore suggest to add it to opm-common |
Okay, utility/convenience is clearly one reason for adding it here. Would it be impossible to make [your/certain use cases] work if it were located elsewhere? Do you, for instance, need access to the internals/private data members or member functions of |
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Exact! For instance, we need access to the automatic differentiation tools within OPM. |
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There are a lot of changes needed here. I have only looked at the C++ code, and I probably missed some. I have not really checked that the activation functions or the layers do what a user of Keras would expect. I have not looked at any of the Python code, someone else must do that.
I have requested many changes, but I hope it provides a useful learning experience. Feel free to ask about anything that is unclear!
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Some comments on the python bits. I think a major point is that the folder opm/ml_tools, which contains only python code, should probably be moved to say the python folder or similar. And since these scripts use external libraries (tf, numpy, keras) I would really like to see a requirements.txt file specifying the versions used. Especially tensorflow is known to be problematic her.
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Thanks all for the valuables comments and suggestions. |
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Integrating Keras capabilities to OPM.
Draft pull request to test/discuss implications of the changes in OPM.
This enables the straightforward and adaptable integration of neural networks into OPM scripts. These models are initially trained using the Keras library in Python, stored in a format readable for the OPM framework and subsequently deployed within OPM.
When the user initializes and loads a stored Keras model inside an OPM script, an automated deployment process handles all the translation. This process works by operating a series of steps handling model interpretation, layer conversion, optimization, and code generation steps to adapt the Keras model to a native OPM function.