[BUG] Monte Carlo dropout does not work with pytorch-lightning >=2.2.0

[eschibli]

Monte Carlo dropout appears to silently fail with the current release of pytorch-lightning.

To Reproduce
See this colab workbook. TCNModel instances with different dropout keywords produce identical CV results and inferences if given the same random_state, even with dropout set to 0.99, which should catastrophically underfit. I was able to reproduce this behaviour on my laptop using this python environment obtained by running pip install darts in a fresh Python 3.11 venv.

Expected behavior
The dropout keyword should impact model results. Extremely high dropout should result in severe underfitting. I was able to obtain this expected behavior in this environment by downgrading pytorch-lightning to 2.1.2. This can also be observed in colab