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underflow in dt nan #244
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There is a min_step argument if you use any RK adaptive-step solver like the default
Depending on your application, it might be worth thinking more about how to model a less stiff ODE though (if that is a possibility). |
Thanks a lot! This error occurs since dt is too small. By setting "min_step": 0.01, it works!
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But this version (enabling setting min_step) hasn't been updated on pip. If we use pip to install torchdiffeq, we still cannot set min_step. |
Hi,
when using dopri5 algorithm, it sometimes occurs "underflow in dt nan". Could we set a upper bound and a lower bound for dt to avoid such problems?
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