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Update class names for Paddle 3.0
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[JAX] XLA Custom Calls with FFI for FusedAttnFwd, Quantize, Transpose, ActLuFP8, LayerNormForwardFP8FFI, and LayerNormBackwardFFI (#1263)

* Add TransposeFFI, test passed
Signed-off-by: Hua Huang <huah@nvidia.com>

* Add ActLuFP8FFI; fix TransposeFFI
Signed-off-by: Hua Huang <huah@nvidia.com>

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

* Add FusedAttnForwardFFI and some unit tests
Signed-off-by: Hua Huang <huah@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



* Minor fix
Signed-off-by: Hua Huang <huah@nvidia.com>

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

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



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

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



* 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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Signed-off-by: Hua Huang <huah@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

[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>

Add THD + GQA supports for cuDNN >= 9.6
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Skip encoder tests on V100

* Fix mulitprocessing jax.distributed.init

* Remove XLA xla_gpu_deterministic_ops which causes segfault

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Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use 64-bit offsets for cuDNN 9.5+
* Align workspace tensors to 16B.
* Fix bug where std::accumulate overflowed on large tensor shapes.
* Only support 64-bit offsets on arbitrary sequence length fp16 backend.
Signed-off-by: Michael Goldfarb <mgoldfarb@nvidia.com>

remove one FA version in the L3 test
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

Remove PyTorch L0 distributed test

Forgot to remove in #1255.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

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

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

* Reorganize PyTorch L1 tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Move ONNX tests to L1
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Move FA version test to L3
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Limit parallel build jobs in FA version test
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

fix seq_dim in CP implementation
Signed-off-by: Xiaowei Ren <xren@nvidia.com>

* register CmdBufferCompatible traits via C++ API

* renamed FFI_Traits

* use register_ffi_target()

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

* fix bias for 0-dim tensor
Signed-off-by: Xin Yao <xiny@nvidia.com>

* add check
Signed-off-by: Xin Yao <xiny@nvidia.com>

* use numel() instead of nullptr
Signed-off-by: Xin Yao <xiny@nvidia.com>

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Signed-off-by: Xin Yao <xiny@nvidia.com>

Fix wgrad for GroupedLinear when weights doesn't require grad
Signed-off-by: Xin Yao <xiny@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

Fix FP8 activation recompute
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>