Open natolambert opened 2 years ago
Not fully understand the normalization you have in mind. Are you referring to passing a set of constant scalars to be applied to the output of the dynamics model?
A set of scalars (can almost use the input normalizers) that map from the raw network outputs to the actual states of the environment.
Two times this was useful:
Maybe its best for me to try it and see how it impacts some basic tests. Not a crucial addition.
Hi, is there any update regarding this? I have also used it in the past and found it to be useful in certain cases. Thanks!
@mohakbhardwaj -- I haven't made the time to make the PR. Happy to provide feedback if you take a stab at it?
🚀 Feature Request
When training non delta-state models, the outputs of dynamics models can take large values (way outside a unit Gaussian). In the past I have tried using output scalars to let the outputs try to learn something close to a unit Gaussian rather than variables with diverse scales.
Motivation
Is your feature request related to a problem? Please describe. I think it would help the PR for the trajectory-based model, #158 .
Pitch
Describe the solution you'd like I think there could be an optional output scalar that acts normally to the input one?
Are you willing to open a pull request? (See CONTRIBUTING) Sure.
Additional context
Add any other context or screenshots about the feature request here.