GitLab

* First draft, for discussion

* Fix mistakes in LAMB equations

* Add loop over chunk

* Bug fix

* Bug fix

* Bug fix

* Undo bug fix

* Bug fix

* Add multi tensor LAMB optimizer to setup.py

* Rename step_size to learning_rate

* Fix compilation errors

* Existing tests passing, still need to add per-tensor tests

* Test is passing, still need to measure performance

* ILP for l2norm functor

* update larc
Signed-off-by: Jason <jasoli@nvidia.com>

* scale_loss fix
Signed-off-by: Jason <jasoli@nvidia.com>

* typo
Signed-off-by: Jason <jasoli@nvidia.com>

* revert LARC

update input size check to fix github issue #262

update SyncBatchNorm count check so that size 1 input with cross GPU
synchronization runs fine.

resolves issue #254

Added input casting for pure python implementation, this supports mismatched
input and layer dtype.

* Support add_param_group

* syntax

* Test added and passing

* fix URLs

* Update distributed.py

* remove unused tens tensor in example/imagenet/main_amp.py

* remove unused tens tensor in deprecated examples and tests/L1

* change .type().ScalarType() to .scalar_type() + at::ScalarType::X to at::kX

* revert scalar_type() to type() for AT_DISPATCH_FLOATING_TYPES_AND_HALF

* revert scalar_type() to type() in AT_DISPATCH_FLOATING_TYPES

* revert scalar_type() to type() for AT_DISPATCH_FLOATING_TYPES_AND_HALF in welford.cu

* revert scalar_type() to type() in layer_norm_cuda_kernel.cu

* revert at::kType  to at::ScalarType::Type

* use DISPATCH_FLOAT_AND_HALF to get rid of warnings

* add dispatch mechanisms for double+float and double+float+half