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			Derivative Informed Neural Operator

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	An Efficient Framework for High-Dimensional Parametric Derivative Learning
  • PDE data generation is handled by FEniCS hIPPYlib, and hippyflow. For this hIPPYlib and hippyflow must be installed.

With conda

  • conda create -n dino -c uvilla -c conda-forge fenics==2019.1.0 tensorflow=2.7.0 matplotlib scipy

Assumes that the environmental variables HIPPYLIB_PATH, HIPPYFLOW_PATH and DINO_PATH have been set.

  • export HIPPYLIB_PATH=path/to/hippylib
  • export HIPPYFLOW_PATH=path/to/hippyflow
  • export DINO_PATH=path/to/dino

Machine learning in Tensorflow (Beware of version / eager execution)

Neural network training is handled by keras within Tensorflow. The way that the Jacobians are extracted at present requires that some tensorflow v2 behaviour is disabled. This creates issues with eager execution in later versions of tensorflow. This library works with tensorflow 2.7.0. In the future, dino may be reworked to handle the eager execution issue in later versions of tensorflow.