Revision 0ee1127c81bf245225cd7db50d631e8677abaefc authored by Sasha Sheng on 08 February 2021, 10:50:33 UTC, committed by Facebook GitHub Bot on 08 February 2021, 10:52:20 UTC
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
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