Question[multi node training]
How to train a  model using multi-node(eg. 2 node, each node with 4gpus, just set the node numbers in the config doesn't work, In the pytorch-lighting tutorial, It needs the parameters like port and rank, etc) ?  Do you have any tutorial or examples like in the speech_to_text_bpe.py?

# Training the model
```sh
python speech_to_text_bpe.py \
    # (Optional: --config-path=<path to dir of configs> --config-name=<name of config without .yaml>) \
    model.train_ds.manifest_filepath=<path to train manifest> \
    model.validation_ds.manifest_filepath=<path to val/test manifest> \
    model.tokenizer.dir=<path to directory of tokenizer (not full path to the vocab file!)> \
    model.tokenizer.type=<either bpe or wpe> \
    trainer.gpus=-1 \
    trainer.accelerator="ddp" \
    trainer.max_epochs=100 \
    model.optim.name="adamw" \
    model.optim.lr=0.001 \
    model.optim.betas=[0.9,0.999] \
    model.optim.weight_decay=0.0001 \
    model.optim.sched.warmup_steps=2000
    exp_manager.create_wandb_logger=True \
    exp_manager.wandb_logger_kwargs.name="<Name of experiment>" \
    exp_manager.wandb_logger_kwargs.project="<Name of project>"
```
