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* Add LayerNormForwardFFI(); add FFI calls in Python
Signed-off-by: Hua Huang <huah@nvidia.com>

* Add FFI for RMS norm, all tests passed
Signed-off-by: Hua Huang <huah@nvidia.com>

* Simplify layer & RMS norm FFI calls
Signed-off-by: Hua Huang <huah@nvidia.com>

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* Simplify tensor size calculations
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Signed-off-by: Hua Huang <huah@nvidia.com>
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rm default value for NVTE_JAX_FUSED_ATTN_WITH_FFI
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* disable fused attn with ffi

---------
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"

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* update docstring and fix max_seqlen logic for thd
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* WIP: add get_max_b/t
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* fix max_seqlen code and docstring
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* sucess: add max_b/max_t
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* 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
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* 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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Update jax version for ffi
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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
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* Add LayerNormForwardFP8FFI & LayerNormBackwardFFI
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* Revise FusedAttnForwardFFI()
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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
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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.
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* register CmdBufferCompatible traits via C++ API

* renamed FFI_Traits

* use register_ffi_target()

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fixed assertion bug for SWA
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Update test to check support for context parallel attention.
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* Expose JAX sliding window attn API
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* No SWA in context parallel; fix RNG seed in test
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* 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
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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
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* Add Padding mask w/ sliding windows sanity tests
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* Use float32 for the reference code softmax calculation
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Implementation of context parallel fused attention using all-gather.
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Signed-off-by: Frederic Bastien <fbastien@nvidia.com>
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* Propagate sm_margin to the underly layernorm kernels

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* implemented custom call with ffi in csrc

* moved headers of misc to misc.h, add ffi.h

* ActLu and DActLu lowering with ffi_lowering

* CastTranspose with ffi_lowering

* enabled cudaGraph

* added 4d input test case to TestActivationLu

* added operand_output_aliases for CastTranspose

* added env var NVTE_JAX_WITH_FFI, default value = 1

* replace casting ActivationEnum by taking its value

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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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* Add enabled() to BasePrimitive

* Add layernorm/rmsnorm fallback

* Add cast_fp8 fallback

* Add transpose/cast_transpose XLA fall back

* Act_lu fallback

* Add transpose fallback

* Add softmax fallback

* Unify the use of _cast_fp8

* Add tests for NVTE_JAX_CUSTOM_CALLS_RE

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* removed singleton wrapper
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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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* Enhance input checks
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* Separate fused attn to 2 differnt APIs and add the docs
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* Fix lint
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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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