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Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

v1.5.0

1 month ago

Version 1.5.0 Release Notes

New Feature: PyTorch Lightning Integration with NeuroMANCER core library. All these features are opt-in.

  • Code simplifications: zero boilerplate code, increased modularity
  • Added ability for user to define custom training logic
  • Easy support for GPU and multi-GPU training
  • Easy Weights and Biases (https://wandb.ai/site) hyperparameter tuning and Tensorboard Logging

v1.4.2

6 months ago

Version 1.4.2 Release Notes

  • New feature: Update violation energy for projected gradient #110 (based on idea #86).
  • Reverted psl.nonautonomous.TwoTank (umin, umax) bounds to (0.5, 0.5) for numerical stability #105
  • Added new unit tests for problem.py and system.py #107
  • Automated docs build from master -> gh-pages #107
  • Fixed positional arg error and added support for Time data in file_emulator.py #119
  • Fixed a bug in System which caused incorrect visualization of the computational graph
  • Minor updates to examples