GitLab

Special thanks to @g-karthik for tracking this issue down.

* Add Linear warmup+decay lr schedule
Update lr schedule unit tests

* LR scheduler unit tests for LR Range Test and 1Cycle

* Disable yapf to preserve parameterizaton

* Disable test_pipe.py for CI debugging

* Disable test_lr_scheduler for CI debugging

* Disable test_lr_scheduler for CI debugging

* Enable all unit tests for CI debugging
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

* Remove a very verbose print statement.

* Update engine.py

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

Co-authored-by: Olatunji Ruwase <olruwase@microsoft.com>

Bumps [nokogiri](https://github.com/sparklemotion/nokogiri) from 1.10.10 to 1.11.0.
- [Release notes](https://github.com/sparklemotion/nokogiri/releases)
- [Changelog](https://github.com/sparklemotion/nokogiri/blob/master/CHANGELOG.md)
- [Commits](https://github.com/sparklemotion/nokogiri/compare/v1.10.10...v1.11.0

)
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Jeff Rasley <jerasley@microsoft.com>

Co-authored-by: Reza Yazdani <reyazda@microsoft.com>
Co-authored-by: Olatunji Ruwase <olruwase@microsoft.com>

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

Allow DeepSpeed models to be initialized with optimizer=None
Co-authored-by: Shaden Smith <Shaden.Smith@microsoft.com>

Co-authored-by: Samyam Rajbhandari <samyamr@microsoft.com>

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

Co-authored-by: Shaden Smith <Shaden.Smith@microsoft.com>

* [doc] xref to hostfile discussion

wasn't clear where to find what was meant by `hostfile` - so adding a link to where it's discussed.

* remove whitespace

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

* Update launch.py

* formatting

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

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

* fix arch flags, add PTX

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

* 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