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Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* test causal mask
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* restrict mha_fill for THD format
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix fused attn with CP and comment out is_alibi code
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* clean up FE0.9 vs FE1.0 FP8 implementations, and related unit tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* change NVTE_FP8_DPA_BWD default to 1, and fix its use in qkvpacked/kvpacked APIs
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix lint and self.tp_size/group in FusedAttention()
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* update FE to 6902c94
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add FP8 MHA support
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* update to FE v1.3.0
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* minor fixes for FP8 MHA with different configs
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* emit stats regardless of is_training
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix linear when input is not Float8Tensor
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix d_out type when f16 bprop
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix user buffer for layernorm_linear/linear and revert two FP8 casts in MHA
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add docstring for fp8_dpa/mha in recipe
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fixes
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* fix backend selection to avoid FA
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* replace transpose with transpose_2d
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* use RMSE for FP8 unit tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* replace two more transpose with transpose_2d
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add FP8 initialization to FusedAttention
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* rm docs
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Revert "add FP8 initialization to FusedAttention"

This reverts commit 15fffd825d6f23f31ea709b16ba01dfd61efabf8.
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Change order of ctxs
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fixes
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* minor fixes
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add back docs and mark as beta
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* minor fixes for tests and docs
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Don't use autograd hook for bwd reduction
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* FP8 cuda graphs
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>
Co-authored-by: Charlene Yang <charleney@nvidia.com>

* Fix numerics
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* exclude torch compile from numerics tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* More numerics fixes
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix CI
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* rm fusion from unfused path
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>
Co-authored-by: Charlene Yang <charleney@nvidia.com>

* Implement fused kernel for FP8 scale update
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add fused kernel for amax and scale update

Add unit test.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Replace paddle.fluid imports with paddle.base
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Move fused kernel to core library
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug test
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use FP8 update kernel in Paddle
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug FP8 scale update in Paddle
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix lint errors
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug Paddle test failures
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Make update kernel in-place for PyTorch
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Revert cudnn-frontend commit
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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Signed-off-by: Tim Moon <tmoon@nvidia.com>
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Experimental FP8 tensor
Co-authored-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Sudhakar Singh <sudhakars@nvidia.com>
Co-authored-by: Przemyslaw Tredak <ptrendx@gmail.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Add fp8 tensor to ci test
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* review comments and tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Minor changes
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Default to FP8 usage
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix docs
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Naming changes
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* minor fix
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix transpose caching
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Debug transpose caching

Handle case where transpose cache is updated externally.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Rename FP8GlobalStateManager.with_fp8_parameters
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* remove Float8Tensor from import API
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Avoid caching FP8 transposes if not required
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix import error in FP8 tensor tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix tranpose caching and checkpointing bug
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Improve caching and fix distopt case
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Update transformer_engine/pytorch/float8_tensor.py
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>

* Remove recursive logic
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix cache reset bug
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Store FP8 attributes in dict

Easier for multiple tensors to share, e.g. detached tensors.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Make sure scale_inv is 1D tensor
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Make sure scale_inv is 1D tensor
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fixes and detach recipe
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Set default fp8 data type
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

---------
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Sudhakar Singh <sudhakars@nvidia.com>
Co-authored-by: Przemyslaw Tredak <ptrendx@gmail.com>

* initial test fix
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Drop eval for selective checkpointing tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Remove redundant recompute for FA
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* CI fix; Decouple fused attention and numerics tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Debug PyTorch and Paddle tests on Ada
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Only run Paddle layer tests with cuDNN fMHA on supported archs
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug PyTorch fMHA tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Reduce JAX FP8 GEMM sizes

Avoid split-k kernels on Ada.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Disable JAX fused self-attention test on Ada
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Run supported fused attention tests on Ada
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Run supported fused attention JAX tests on Ada
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Enable Paddle fused attention on Ada
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Update reference scale calculation in TensorFlow test
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Restore backend support to reference FP8 attention impl in PyT test

Review suggestion from @cyanguwa
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix merge conflicts
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug Paddle tests on Ada
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Loosen tolerances for Paddle attention tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Assume causal mask implies equal seqlens in Paddle attention tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Change scaling factor from E8M0 to E8M23
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* fix formula
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Signed-off-by: Sangkug Lym <slym@nvidia.com>

* Initial refactor
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Reorder methods by purpose
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Save full global state
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* More fixes to test
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Optimize calls to .cpu() during checkpointing
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fixes for ONNX
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Use torch.compile for version 2.0 and higher
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Address review
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Remove unused import
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* use torch.__version__
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Use NVFuser for dropout fusions
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix onnx tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Fixes in nested autocast
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>