Comments (1)
Thank you for your interest! We're not planning on merging this into PyTorch just yet, as we're still working on implementing some more modern solvers (one of which actually slipped our attention and silently made it into the release..) and tuning them for better performance. We'd like to keep iterating with our own repo for now.
I understand your concern about extra installations with the growing amount of external scientific libraries built around PyTorch, but I think of that as a boon so each library can be maintained separately, apart from core PyTorch.
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Related Issues (20)
- RuntimeError: Mismatch in shape: grad_output[0] has a shape of torch.Size([1, 2404, 4]) and output[0] has a shape of torch.Size([1, 1963, 4]).
- learn_physics.py is very bad.
- code for reproducing Fig. 8
- Making forward function different than backward function
- reuse solver object
- Integrate Forced Andronov-Hopf Bifurcation HOT 3
- Export to ONNX?
- Is func variable in odeint(func, y0, t) the derivative part of the ode?
- Initial Condition changes when calling the odeint_adjoint
- How to use the summary function for model description?
- How to work with control namely PID controller
- Why odeint sometimes provides a wrong solution? HOT 5
- Non uniform time step in example/ode_demo.py
- runtime of ode_demo.py using adjoint vs. not using it HOT 1
- underflow in dt nan HOT 4
- Typo in paper (?) HOT 1
- How to pass extra paramaters of func to odeint? HOT 2
- Bug: Memory Leaky with from torchdiffeq import odeint HOT 1
- Perform one integration step HOT 2
- Scipy LSODA for stiff ODE
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