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* remove pyprof

* remove reparameterization

* remove pyprof test

* clean up

Co-authored-by: Piotr Bialecki <pbialecki@nvidia.com>
Co-authored-by: Eddie Yan <eddiey@nvidia.com>
Co-authored-by: Rishi Puri <riship@nvidia.com>
Co-authored-by: Sangkug Lym <slym@nvidia.com>

use __launch_bounds__(1024) for multi_tensor_apply, re-enable skipped tests

* fix warp size in WARP_SHFL* in layernorm

* enable fused_layer_norm tests on ROCm

* enable mlp cuda

* add setup changes and tests

* skip the unit tests

* updated conditions for empty array

* removed hip platform conditions

FusedSGD now work as before
FusedAdam now work with o1/o2, no longer fuse scaling and casting
Removed special backend handling for FusedAdam
Moved and updated test for FusedAdam into run_optimizers
Removed legacy tests for optimizers.FP16_optimizer and FusedAdam in run_mixed_adam

Co-authored-by: Aditya Agrawal <aditya.iitb@gmail.com>
Co-authored-by: Marek Kolodziej <mkolod@gmail.com>

This commit adds an FP16Model class as a successor to network_to_half.

The benefits of this class are:

- Preservation of single-precision for BatchNorm layers. The models
  generated by network_to_half() convert BatchNorm moment tensors to
  half-precision, then back to single-precision, which hurts the
  accuracy of the moment estimators and occasionally results in NaNs.
- Support for multi-argument nn.Modules (self-explanatory from code).

* Add unittest for FusedAdam.

* Fix some bugs.

* set seed for adam test