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* Implement ring attention primative for Jax.
Signed-off-by: Michael Goldfarb <mgoldfarb@nvidia.com>
Signed-off-by: Ming Huang <mingh@nvidia.com>

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Signed-off-by: Michael Goldfarb <mgoldfarb@nvidia.com>
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* added prepare phase for the FusedAttnForwardFFI

* enabled FusedAttnForwardFFI by default

* moved prepare phase into pybind

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

rm default value for NVTE_JAX_FUSED_ATTN_WITH_FFI
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* disable fused attn with ffi

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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* lowering a dict of attrs

* improve err message with line and func info

* implement a product() for ffi dimensions

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* WIP: add max_t support for THD
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* WIP: save tensors for debug and point to new FE
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* fix stats in bwd
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* fix stats in fwd
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* add docstring for DPA
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* add docstring
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* WIP: first try on adding max_b and max_t
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* Revert "[pre-commit.ci] auto fixes from pre-commit.com hooks"

This reverts commit c3d522e9f5aef3c8ddfec5bf6ff24c3db97bb059.
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* Revert "WIP: first try on adding max_b and max_t"

This reverts commit 3bc01ebaf2aa846fd16634e2d33b0d0f5803a076.
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* update docstring and fix max_seqlen logic for thd
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* revert two lines of change in docstring
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* WIP: add get_max_b/t
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* fix max_seqlen code and docstring
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* sucess: add max_b/max_t
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove debug code
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* change max_b/max_t buckets
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* fix b vs orig_b
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* fix b vs orig_b with 0 fill
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* update FE for T3HD/TH3D
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* add max_b to conversion kernels
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* fix lint
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* fix changes after last merge
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* add Jax support for max_t
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* update FE to 1.8.0-rc
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* update FE to 1.8.0
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* code review/formating fixes
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* fix Stats shape for <9.6
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* return nullptr for offset_stats when cudnn < 9.6
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* add more version control
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[JAX] XLA Custom Calls with FFI for FusedAttnFwd, Quantize, Transpose, ActLuFP8, LayerNormForwardFP8FFI, and LayerNormBackwardFFI (#1263)

* Add TransposeFFI, test passed
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* Add ActLuFP8FFI; fix TransposeFFI
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* Add QuantizeFFI
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* Add FusedAttnForwardFFI and some unit tests
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* Minor fix
Signed-off-by: Hua Huang <huah@nvidia.com>

* Add LayerNormForwardFP8FFI & LayerNormBackwardFFI
Signed-off-by: Hua Huang <huah@nvidia.com>

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* Revise FusedAttnForwardFFI()
Signed-off-by: Hua Huang <huah@nvidia.com>

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* Add FFI_CudaGraph_Traits

All tests passed, ready for merge
Signed-off-by: Hua Huang <huah@nvidia.com>

* Bug fix for FFI data type mismatch

Also add a safeguard on the entrance to FFI function
Signed-off-by: Hua Huang <huah@nvidia.com>

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[JAX] Fix correctness of JAX fused attention with CP and improve numerics check in unit tests (#1282)

Fix correctness of JAX fused attention with CP.
Signed-off-by: Michael Goldfarb <mgoldfarb@nvidia.com>

fixed assertion bug for SWA
Signed-off-by: Md Fahim Faysal Khan <mdfahimfaysa@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
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Update test to check support for context parallel attention.
Signed-off-by: Michael Goldfarb <mgoldfarb@nvidia.com>

* Expose JAX sliding window attn API
Signed-off-by: Hua Huang <huah@nvidia.com>

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* No SWA in context parallel; fix RNG seed in test
Signed-off-by: Hua Huang <huah@nvidia.com>

* Handle SAW API discrepancy in cuDNN and Python
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* Add SAW API for flax, all tests passed

Will update tests/jax/test_praxis_layers.py next
Signed-off-by: Hua Huang <huah@nvidia.com>

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* Update test_praxis_layers.py for SWA, test passed
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* Use tuple window_size; update for PR #1212
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* Add and adjust some pytest.skip
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* Revised following Reese Wang's comments

Still need further debugging:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-KV_PACKED-NO_MASK-NO_BIAS] - AssertionError:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-KV_PACKED-NO_MASK-POST_SCALE_BIAS-1HSS] - AssertionError:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-SEPARATE-NO_MASK-NO_BIAS] - AssertionError:
FAILED test_fused_attn.py::TestFusedAttn::test_backward[NO_SWA-DROP_0.0-4-128-256-16-16-64-BF16-CROSS-SEPARATE-NO_MASK-POST_SCALE_BIAS-1HSS] - AssertionError:

These errors does not exist in the previous commit
Signed-off-by: Hua Huang <huah@nvidia.com>

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* Fix no-SWA test case errors in previous commit
Signed-off-by: Hua Huang <huah@nvidia.com>

* Add Padding mask w/ sliding windows sanity tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use float32 for the reference code softmax calculation
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Implementation of context parallel fused attention using all-gather.
Signed-off-by: Michael Goldfarb <mgoldfarb@nvidia.com>

Signed-off-by: Frederic Bastien <fbastien@nvidia.com>
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* Support non-deterministic algo
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* Refine the helper function name
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* Move fixture to conftest.py
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* Support actlen = 0 after cuDNN 9.3.0
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* Add runtime_segment < max_segment tests
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* Integrate experimental ragged offset
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* Use per sequence based offsets
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* Format
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* Remove v/o_seq_offsets
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* Add FP16 sanity tests and remove forward tests from the automatically run tests
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* Enhance input checks
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* Separate fused attn to 2 differnt APIs and add the docs
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* Add experimental to the docs
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* Fix lint
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* Add runtime segments check
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* Remove finished TODO
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* Apply formatting
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* Apply formatting
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* Splitted cpp_extensions.py, renamed mlp.py and fused_attn.py
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* fixed import in tests
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