Fix wrong behavior of DDPStrategy option with simple GAN training using DDP

[samsara-ku]

What does this PR do?

Fixes #20866 #20328 #18740 #17212

This PR adds MultiModelDDPStrategy class and its simple execution example, for the multi-gpu training with GAN training.

Simply speaking:

* right way using DDP in pytorch.
# each model is divided and wrapped by DDP class
generator, discriminator = DDP(generator), DDP(discrimiantor)

* current pytorch-lightning GAN training.
# trainer contains two nn.Modules; generator and discriminator
DDP(trainer) -> trainer contains two nn.Modules; generator and discriminator

* proposed `MultiModelDDP` class can use this way.
# trainer also has two nn.Modules, generator and discriminator;
# this way allocate DDP class to the each model in the trainer, not the trainer.
MultiModelDDP(trainer)

• Currently, pytorch lightning simple GAN training has has problem with DistributedDataParallel strategy. It tries to wrap pl.trainer, not the nn.Module models in the pl.trainer

• Although we can activate find_unused_parameters=True options to avoid this issue but it is not right way; I think it is just a trick.

• So the key idea to solve this issue is that we assign DistributedDataParallel to the each model in the pl.trainer, different from the previous strategy DDPStrategy.

• I already tested with my GPUs to visaulize the result and tracked the gradients of model with each epoch; it works and you can see the visulized result in thie google drive link

Before submitting

• Was this discussed/agreed via a GitHub issue? (not for typos and docs)
• [v] Did you read the contributor guideline, Pull Request section?
• [v] Did you make sure your PR does only one thing, instead of bundling different changes together?
• Did you make sure to update the documentation with your changes? (if necessary)
• Did you write any new necessary tests? (not for typos and docs)
• Did you verify new and existing tests pass locally with your changes?
• Did you list all the breaking changes introduced by this pull request?
• Did you update the CHANGELOG? (not for typos, docs, test updates, or minor internal changes/refactors)

PR review

Anyone in the community is welcome to review the PR.
Before you start reviewing, make sure you have read the review guidelines. In short, see the following bullet-list:

Reviewer checklist

• Is this pull request ready for review? (if not, please submit in draft mode)
• Check that all items from Before submitting are resolved
• Make sure the title is self-explanatory and the description concisely explains the PR
• Add labels and milestones (and optionally projects) to the PR so it can be classified

---

📚 Documentation preview 📚: https://pytorch-lightning--20936.org.readthedocs.build/en/20936/

[stale]

This pull request has been automatically marked as stale because it has not had recent activity. It will be closed in 7 days if no further activity occurs. If you need further help see our docs: https://lightning.ai/docs/pytorch/latest/generated/CONTRIBUTING.html#pull-request or ask the assistance of a core contributor here or on Discord. Thank you for your contributions.

[Borda]

@SkafteNicki could you pls check too :)

[SkafteNicki]

could we add one or two tests similar to
https://github.com/samsara-ku/pytorch-lightning/blob/ece7d38abb908e96eb72af363606d2585e8843f2/tests/tests_pytorch/strategies/test_ddp_integration.py#L40-L66
that actually tests that the new strategy works with trainer.fit as expected

[samsara-ku]

Sorry for bothering you, I'll add more concrete test case.

[Borda]

@samsara-ku please mark also the comments as resolved to keep track what has left :)