For example, I have a model that includes torch.nn.Dropout
layers that behave differently during training and evaluation. In Torch, I need to use model.train()
or model.eval()
to set which mode the model should be in. Is this also done by RLlib if I use a custom_eval_fn
or the default routine?
Hi @LukasNothhelfer,
The Torch trainer switches between eval and train modes in
compute_actions
and
learn_on_batch:
If you are using the standard way to customize, for example using “with_updates” then it should be switched. You could add break points or print statements there if you want to be extra sure.
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+1 for sharing code references, thx