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* Updating BLOCK_SIZE to 1024.
tests/L0/run_optimizers/test_fused_optimizer.py test passes except for bfloat16 for Adam. There seems to be a bug in this test that needs to be resolved.
For now skipping test_bfloat16 for Adam in the unittest.
Ran 17 other tests and ALL other tests pass!
More details on the effects of these changes can be found here -  https://confluence.amd.com/display/MLSE/Apex+Kernel+Optimization

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This commit changes BLOCK_SIZE=1024 ONLY FOR different optimizers.
L2norm kernels (part of LAMB optimizer algorithm) still maintain BLOCK_SIZE=512 otherwise Allclose fails.

* Updating tests/L0/run_optimizers/test_fused_optimizer.py with @skipifRocm to skip test_bfloat16 in Adam.
Co-authored-by: aspanday <aspanday@amd.com>

* Add fused mixed precision lamb optimizer.

* Fix device usage in constructor.

* Fix sending param_group tensor state to device.

* Remove unneeded device set.

This reverts commit bdd481d1.

* 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

* Pushing for build tests

* Contrib files

* Removing deprecated checks

correctly not apply bias correction to epsilon(same as recent upstream change)
correctly not apply bias correction to weight decay(consistent with upstream AdamW)
Make adam_w_mode for FusedAdam/LAMB, to do L2 or Weight Decay (Adam vs AdamW)
Correct document reg_inside_moment differently from adam_w_mode in FusedNovoGrad
Removed legacy eps_mode from FusedAdam
Make internal math type float across fused optimizers