GitLab

* fix dropout scaling from p to 1/(1-p) (#816)
Co-authored-by: Sukru Eryilmaz <seryilmaz@computelab-dgx1v-32.nvidia.com>

* Improvements to apex.mlp (#804)

* update fused bias relu backward kernel

* adding support for not require first layer dgrad

* fix bug: wrong layer in requires grad

* add infrastructure for optional bias and activation, currently only support no bias and no relu

* make bias and relu optional separately

* add sigmoid activation option

* enable wider load/store for multi_tensor_apply kernels (#763)

* modify MTA axpby for wider load/store

* Make scale/axpby/l2/adam/lamb multi_tensor uses wider load

* Changes to make xentropysoftmax load/store vectorized when possible: (#725)

* Changes to make xentropysoftmax load/store vectorized when possible:
Increase default ILP so that each thread handle 16 Bytes data in one step
Make thread load/store longest vector possible
Make unroll case handle adjacent data instead of strided...

* modify MTA axpby for wider load/store

* Make scale/axpby/l2/adam/lamb multi_tensor uses wider load

* Refactor to allow more flexible treatment of multiple optimizers/models/losses

* Adding _process_optimizers.py

* Created L0 tests (now passing).

* fix: minor print typo (#234)

* make L1 results easier to read

* L0 multiple model/optimizer/loss test fleshed out

* Adding test that master params remain synced across distributed processes

* Docstring updates

* Docstring updates