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* Switch from deprecated allreduce interface.

* Make pipeline checkpoint files portable.

RTX-30 series are compute_86
```
python -c "import torch; print(torch.cuda.get_device_capability())"
```
This PR adds support for this compute capability.

Reference: https://developer.nvidia.com/cuda-gpus

Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

* 1) Register layout as buffer of module so that we can save/load checkpoint; 2) Add a broadcast of layout at the beginning to ensure different processes will have consistent layout during distributed training.

* Add docstring for max_seq_length argument in SparseSelfAttention
Co-authored-by: Zhun Liu <zhunliu@microsoft.com>
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

* [cifar tutorial] improve readability 

* tracking optimizer step in cpu-adam when loading checkpoint

* add warning/error message for updating optimizer step count

* resolve build issue

* supporting state update from the python side

* track step from python in all cases

* remove comma

* supporting different hidden dimensions

* add support for larger hidden dimensions (greater than 8K)

* remove empty line

* add loop unrolling factor for dropout kernels

* update different kernels based on the reviews
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

This PR:
* fixes a misspelled method name
* also `( () )` doesn't read too well, until one reads the code and understands that it's not a formatting bug. I proposed to simply say that it's a callable object.

Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

In the absence of a model parallel group, model_parallel_allreduce should not do any reduction. This commit fixes the bug which was doing a model parallel allreduce across world group when model parallel group is None

* Use zero-tensors for missing gradients to avoid size mismatch

* Unit test for unbalanced gradients in ZeRO

* Formatting fixes

* Use AML method to set env vars instead of using mpi4py.
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

* Add guard to not using `torch.version.cuda` above no-CUDA environment.
* Fix several typos on setup.py.
Signed-off-by: Seunghwan Hong <seunghwan@scatterlab.co.kr>
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

* zero-1 memory fix

* auto-tune max elems per comm to reduce padding/comm intervals

* clean-up and added previously missing reduction options

* fix testing backing to work with torch1.7

* Fix layout bug in ZeRO Stage 1 checkpoint logic
Add elastic checkpoint option for ZeRO stage 1, default to True

* Format fixes

* remove cpu-feature

* remove psutils requirement

* Adds torch install requirement to documentation.

* build ops documentation

* on cpu box error gracefully if cuda home doesn't exist

* gaurd against torch import issue

* fix sytax error

* fix import