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You're right that make_adv_reg_config doesn't have such parameter for delaying the adversarial training. Instead, you may train a base model for a few epochs before wrapping it with nsl.keras.AdversarialRegularization. This achieves the desired behavior because an AdversarialRegularization-wrapped model and its base model share the model variables. The following code snippet illustrates this idea:
I want to train the model without adversarial attack at the first two epochs.
After that, I would like to train the model with adversarial learning.
In summary,
1 epoch: Training w/o adversarial
2 epoch: Training w/o adversarial
3 epoch: Training with adversarial
4 epoch: Training with adversarial
....
Is it possible to adjust the start epoch of the adversarial training?
I couldn't find any related parameter in
nsl.configs.make_adv_reg_config
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