GitLab

* initial commit, dummy training loop, pure pytorch but not DDP

* probably slightly broken, but rough DDP benchmark run

* adding the torchvision requirement for testing

* brainfart

* reduce the loss, do something slightly distributed

* Some cleanup, distributing the training on two GPUs

* some cleanup + adding a vanilla run, still not good to go

* less silly defaults, gtg for a start I think

* smaller batch to fit the smaller gpus used in the circleci rigs

* Adding some options for the benchmark, and regression testing

* [test] set torch seed for Adam tests (#49)

Set the torch seed for tests. xfail mixed precision and memory-efficient mixed-precision state_dict tests due to their states being cast to FP16 and back to FP32 during load_state_dict.
Co-authored-by: Jun Ru Anderson <andersonic@fb.com>

* linting, I really need to automate this isort insanity
Co-authored-by: Jun Ru Anderson <33384298+andersonic@users.noreply.github.com>
Co-authored-by: Jun Ru Anderson <andersonic@fb.com>

Set the torch seed for tests. xfail mixed precision and memory-efficient mixed-precision state_dict tests due to their states being cast to FP16 and back to FP32 during load_state_dict.
Co-authored-by: Jun Ru Anderson <andersonic@fb.com>

Allow training with optimizer state in fp16. Use an enum to select from full-precision, mixed precision, memory efficient mixed precision and pure fp16. Improve clarity of testing code
Co-authored-by: Jun Ru Anderson <andersonic@fb.com>

Add support for mixed-precision (half precision params, full precision gradients) and memory-efficient (half precision params and half precision gradients) training with Adam
Co-authored-by: Jun Ru Anderson <andersonic@fb.com>

Add FusedAdam, update benchmark and add tests.
Co-authored-by: Jun Ru Anderson <andersonic@fb.com>