All the dependencies are standard python packages:
- Pytorch, Numpy, Matplotlib, PIL (used for visualization)
- _*.py: Some common classes/functions used for training and testing.
- _constraint_net.py: A simple network used to represent the constraints to be learned
- _iterative_proj.py: The iterative projection to solve the constrains
- _training.py: Utils used for training
- _dataloader.py: Load training data
- _run_simulation.py: Run simulation use the learned constraint net and the projection operator
- training_*.py: Train the model.
- Data used for training can be found in this shared google drive folder.
- The trained models are in \model folder.
- simulation_*.py: Use the trained model to generate simulations.
- Simulation results will be written to \results folder.
- In "evaluation" branch, simulation scripts are modified to run multiple simulation samples