Summary:
* pytorch lighting stub mostly involving training
* Tests for lightning trainer included
* built on top of the mmf grad accumulation fix: https://github.com/facebookresearch/mmf/pull/747

- [X] MVP 0. Training: Goal - Train a model from scratch and reach similar accuracy as using mmf_trainer
   - [X] Setup the training pipeline: done
   - [X] Training on the right device: done
   - [X] Clip gradients: done
   - [X] Optimizer: done
   - [X] FP16 Support: done
   - [X] LR scheduler (incl. warmup etc): done
   - [X] testcase: train visual_bert on vqa from scratch fo 10 iterations, compare the value: done
- [x] tests included in this PR (tests are only done for pytorch lightning integration):
   - [X] Vanilla Training w/o grad accumulate, make sure loss for 5 iters are the same between mmf and pl
      - [X] Optimizer working as intended as a part of this PR.
   - [X] `max_updates` and `max_epochs` calculation
   - [x] Training with grad accumulate
   - [x] Training with LR schedule achieves a different value compared to without LR schedule
   - [x] Training with LR schedule for PL is the same as training with LR schedule for `mmf_tranier`
   - [x] Training with gradient clipping make sure all grads are within the `grad_clipping` threshold
   - [x] Training with gradient clipping is the same as training with gradient clipping for `mmf_trainer`

Pull Request resolved: https://github.com/facebookresearch/mmf/pull/748

Reviewed By: apsdehal, simran2905

Differential Revision: D26192869

Pulled By: ytsheng

fbshipit-source-id: 203a91e893d6b878bbed80ed84960dd059cfc90c