Make `swa_lrs` as required inside `SWACallback`

[rohitgr7]

Proposed Enhancement

Currently when swa_lrs is not set here:
https://github.com/PyTorchLightning/pytorch-lightning/blob/e3820da28a0cd0982dd1c65d7da1a0e2180454c1/pytorch_lightning/callbacks/stochastic_weight_avg.py#L34-L38

we initialize it to the optimizer lrs here:
https://github.com/PyTorchLightning/pytorch-lightning/blob/e3820da28a0cd0982dd1c65d7da1a0e2180454c1/pytorch_lightning/callbacks/stochastic_weight_avg.py#L167-L168

but during SWALR scheduler update, the values won't be updated because alpha here will be canceled out.

https://github.com/pytorch/pytorch/blob/bf233aa049c4b479fd6cb19f9b8672bb2d42b0e2/torch/optim/swa_utils.py#L281-L286

Motivation

If we keep it as it is, it will lead to issues like this: #9453

Pitch

Make swa_lrs in the callback as required since it's a required parameter in SWALR too and don't initialize it with any default.
https://github.com/pytorch/pytorch/blob/bf233aa049c4b479fd6cb19f9b8672bb2d42b0e2/torch/optim/swa_utils.py#L231

Additional context

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cc @Borda @justusschock @awaelchli @akihironitta @rohitgr7 @carmocca

[felipemello1]

Hi @rohitgr7 , I think that maybe the solution can be improved and simplified. As an user, I already have my learning rate scheduler. I dont want to have to figure out what my learning rate should be at epoch*0.8 and use this LR an starting point. Instead, if there is already a scheduler, just dont override it with SWA scheduler.