What does this PR do?

This PR adds support to learning rate scheduling in Adversary, borrowing the optimization utils from LitModular.

This PR also adds ReduceLROnPlateau as an example.

Type of change

Please check all relevant options.

[ ] Improvement (non-breaking)
[ ] Bug fix (non-breaking)
[x] New feature (non-breaking)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Please describe the tests that you ran to verify your changes. Consider listing any relevant details of your test configuration.

[x] pytest
[ ] CUDA_VISIBLE_DEVICES=0 python -m mart experiment=CIFAR10_CNN_Adv trainer=gpu trainer.precision=16 reports 70% (21 sec/epoch).
[ ] CUDA_VISIBLE_DEVICES=0,1 python -m mart experiment=CIFAR10_CNN_Adv trainer=ddp trainer.precision=16 trainer.devices=2 model.optimizer.lr=0.2 trainer.max_steps=2925 datamodule.ims_per_batch=256 datamodule.world_size=2 reports 70% (14 sec/epoch).

[x] The title is self-explanatory and the description concisely explains the PR
[x] My PR does only one thing, instead of bundling different changes together
[ ] I list all the breaking changes introduced by this pull request
[x] I have commented my code
[ ] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes
[x] I have run pre-commit hooks with pre-commit run -a command without errors

Make sure you had fun coding 🙃