Return output dictionary in LitModular steps

[mzweilin]

What does this PR do?

This PR changes the return of training/validation/test_step() by returning the full dictionary, so that Callback can visualize the intermediate representations in the hooks of on_training/validation/test_batch_end().

This is useful because Lightning can only log scalar data. We need customized callbacks to log media data, such as image and text.

I wonder if we should detach all tensors except the loss to avoid memory leaks. I don't observe any difference in running the test workload CUDA_VISIBLE_DEVICES=0 python -m mart experiment=CIFAR10_CNN_Adv trainer=gpu trainer.precision=16.

Type of change

Please check all relevant options.

• Improvement (non-breaking)
• Bug fix (non-breaking)
• New feature (non-breaking)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

Testing

Please describe the tests that you ran to verify your changes. Consider listing any relevant details of your test configuration.

• pytest
• CUDA_VISIBLE_DEVICES=0 python -m mart experiment=CIFAR10_CNN_Adv trainer=gpu trainer.precision=16 reports 70% (21 sec/epoch).
• CUDA_VISIBLE_DEVICES=0,1 python -m mart experiment=CIFAR10_CNN_Adv trainer=ddp trainer.precision=16 trainer.devices=2 model.optimizer.lr=0.2 trainer.max_steps=2925 datamodule.ims_per_batch=256 datamodule.world_size=2 reports 70% (14 sec/epoch).

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• I have added tests that prove my fix is effective or that my feature works
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