question: Setting random seed before training
context: Hi,
  Do I need to manually set the random seed to ensure the synchronization of state (e.g. initialized parameters) across processes when using distributed training?
answer: No, parameters get broadcast on the first time the model performs forward. This is implemented in the PyTorch DistributedDataParallel wrapper and so applies to Lightning as well.