* add lr scheduler for stable diffusion training
* add lr scheduler test
* rerun ci
* rerun CI
* use np for testing
* move test to CI path
* remove unneeded copy
* working PolynomialDecayWithWarmup + tests.......
add lars_util.py, oops
* keep lars_util.py as intact as possible, simplify our interface
* whitespace
* clean up
* clean up
* asserts
* test polylr for full resnet training run
* add comment
* rename
* fix do_optim
* don't cast lr
* info
* calculate from train_files
* skip it
* lars optimizer + tests
* fix skip list!
* use id to compare in skip list
* go back to using set
* Tensor(bool) * Tensor(bool) is and
* don't lint external/mlperf_resnet
* whitespace
* add external_test_optim to opencl tests
* give mlperf task a name
* mlperf under onnx
* remove track_gnorm
* contiguous instead of realize
* assert momentum and weight decay positive
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Co-authored-by: chenyu <chenyu@fastmail.com>
