text: Title: Update pytorch lightning import to work with Ray and other libraries.
  Body: **Is your feature request related to a current problem? Please describe.**
  Importing and using  `lightning.pytorch` and `pytorch_lightning` in the same program causes conflicts. Ray has migrated their tuning to `ray.tune.Tuner` and is deprecating `ray.tune.run`. Ray uses a conditional import, importing `pytorch_lightning` only if the other is not available. However, it will import `lightning.pytorch` first, where the darts `pl_forecasting_module` imports pytorch_lightning. This may also apply to other places. 
  
  **Describe proposed solution**
  Darts should incorporate a conditional import that matches this priority in `pl_forecasting_module`, `lr_finder`, etc as follows:
  
  ```python
  #import pytorch_lightning as pl
  def import_lightning():  # noqa: F402
      try:
          import lightning.pytorch as pl
      except ModuleNotFoundError:
          import pytorch_lightning as pl
      return pl
  
  pl = import_lightning()
  ```
  
  Note that files may import more than just `pl` - those other imports could also be wrapped under the conditional.
  
  **Describe potential alternatives**
  Change imports of pytorch_lightning to lightning.pytorch
  
  **Additional context**
  I noticed this issue when attempting to use `ray.tune.Tuner` and `ray.train.torch.TorchTrainer` in conjunction with `RNNModel`. I solved it by making the change in the proposed solution.
  