How to make stages?
Hi! Thank you for a great framework! I've tried to write down stages for training. E.g. in my config:
    <<: *default

  stage2:
    <<: *default

    datasets:
      <<: *datasets
             # 240k
      root: ['path1',
             'path2,
             'path3]
      per_folder_ratio: [1.0, 1.0, 1.0]
      transform:
        <<: *transform
        augs_lvl: "light"

    optimizer:
      class_name: RAdam
      lr: 0.0001

and in train.py:
    for stage_name, stage in selected_stages.items():
        print(f"running stage {stage_name}")
        model = build_model(stage) # BUILD LIGHTNING MODULE from func

        trainer = build_trainer(stage_config=stage,
                                module=model,
                                ...) # MAKE pytorch_lightning Trainer using this model
        trainer.fit(model)

I'm using early stopping which make one iteration in aforementioned loop (another way which i'm also tried is to wait max_epochs epochs).
The problem is that second call to trainer.fit initializes DDP one more time and program is crashing because ip address is not freed from previous DDP init.
RuntimeError: Address already in use
I've tried master version of pytorch lightning but the problem did not dissapear