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* Expose JAX sliding window attn API
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



* 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
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 SAW API for flax, all tests passed

Will update tests/jax/test_praxis_layers.py next
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



* Update test_praxis_layers.py for SWA, test passed
Signed-off-by: Hua Huang <huah@nvidia.com>

* Use tuple window_size; update for PR #1212
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 and adjust some pytest.skip
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



* 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>

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

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



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

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

* Propagate sm_margin to the underly layernorm kernels

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Co-authored-by: Phuong Nguyen <36155692+phu0ngng@users.noreply.github.com>

* 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

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

* Support non-deterministic algo
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refine the helper function name
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move fixture to conftest.py
Signed-off-by: Reese Wang <rewang@nvidia.com>

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Co-authored-by: Phuong Nguyen <36155692+phu0ngng@users.noreply.github.com>

* Integrate experimental ragged offset
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use per sequence based offsets
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Remove v/o_seq_offsets
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add FP16 sanity tests and remove forward tests from the automatically run tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance input checks
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Separate fused attn to 2 differnt APIs and add the docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add experimental to the docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Add runtime segments check
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Remove finished TODO
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

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

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

* categorized `csrc/modules.cpp`
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* adapted the build tool
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

* renamed gelu to act

* added relu, srelu, qgelu

* fixes initialization for layernorm_fp8_mlp tests

* moved activation_fp8 prim into testunit file

* Moved NVTE_Activation_Enum to common/.../activation.h

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

* templated primitives and respective C++ functions
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* fixes for LayerNormMLP, tests in test_custom_compute all passed
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* added default arg for pybind get_workspace_size funcs
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* fixes for TestTransFormer with non-gated act tests
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* renamed gelu to act
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* improved enum implementation, avoid using magic numbers
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* Exposed C++ ActivationEnum to python side
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* Changed error messages
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* changed conditional check on input shape for dbias_cast_transpose
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* changed dtype (tol) for bias grad tests
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* fixes so that layer_norm_fp8_mlp can take bias = None
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* Set bias = None in flax modules
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

* Implemented swiglu and silu
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* Renamed nvte-*silu to nvte-*swish + generalized GetDBiasDact functions
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* combined layernorm_geglu with layernorm_gelu into fused_layernorm
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* fixes to pass all unit tests in test_custom_call_compute.py,
test_layer.py, and test_praxis_layer.py
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* cleaning and formatting
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* renaming based on reviewers suggestions
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* implemented partial fused layernorm
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* geglu + bias passed tests
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* added partial fused calculation for dbias_1
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* clean up
Co-authored-by: Alp Dener <adener@nvidia.com>
Signed-off-by: Phuong Nguyen <36155692+phu0ngng@users.noreply.github.com>

---------
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>
Signed-off-by: Phuong Nguyen <36155692+phu0ngng@users.noreply.github.com>
Co-authored-by: Alp Dener <adener@nvidia.com>

* Allow multi-dims for dgamma and dbeta in LN descriptor.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix the jit error in examples/jax
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Remove unused headers
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Unify the fused attn workspace size cpp code
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Reduce the skipped cases
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Rename self/cross attention to qkvpacked/kvpacked
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update attention mask docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refine the attn mask implementations
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* added support for arbitrary bias shapes for fused_attn
Signed-off-by: Alp Dener <adener@nvidia.com>

* Fix linting
Signed-off-by: Alp Dener <adener@nvidia.com>

* Add b1ss/bhss/11ss bias shapes when not requiring dBias
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* fix lint
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* add bias_b/h to plan cache
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* fixed compile errors after PR653 merge
Signed-off-by: Alp Dener <adener@nvidia.com>

* updated JAX unittests for new bias shapes
Signed-off-by: Alp Dener <adener@nvidia.com>

* fixed mismatched mask type checking
Signed-off-by: Alp Dener <adener@nvidia.com>

* corrected skip condition
Signed-off-by: Alp Dener <adener@nvidia.com>

* fix selection logic for A100s
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* corrected skip checks for bias shapes
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* resolved test issues but neginf with float16 is still problematic with JAX
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* new bias shapes passing TE JAX CI for seqlen <= 512, seq_q == seq_kv and h_q == h_kv conditions
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* TE/JAX fused attn tests for new bias shapes passing with neg_inf=-2**27 for Bfloat16 and -2**15 for Float16
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* code style fixes and test parameter ID cleanup
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* fixed incorrect skip condition for backward fused attn test
Signed-off-by: Alp Dener <adener@nvidia.com>

---------
Signed-off-by: Alp Dener <adener@nvidia.com>
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>
Co-authored-by: Alp Dener <adener@nvidia.com>

* Refine MHA API
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Reuse func from the flax
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* qkv packed draft
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix test_layer with fused attn
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add attn_bias_type and enhance a few code flow
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move scale_factor from __call__ to init
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* Enhance the docs
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* Add DPA public API and tests
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* Refine docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

* Add qkv separate fused attn
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* Apply BSHD_BSHD_BSHD format
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* Remove debug log
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* Add fused attention layer tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add NVTE_FUSED_ATTN docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fine-grained fused attn settings
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* Remove the default value of num_attetnion_head and head_dim
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add teardown for fused attn env
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* Unify the Optional notation
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* Fix Pre/Post scale bias comments
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add no_mask tests
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* Add checkpoint_name for fused attn
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* Fix the fused attn batcher
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Adding support of sequence parallelism
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding RoPE
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix wrong batch_logical_axes
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Rnaming FSDP outer env var
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* Poring RoPE to Praxis layers.
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* Porting GeLU + [FP8 Cast].
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* WAR to make XLA successfully match FP8 GEMM on FFN1 with GeLU.
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* Allowing arbitrary dimension of NVShape for the workspace allocation
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* Adding checkpoint_name to fused functions of mlp.py to get better perf with nn.scan.
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* Modify with review feedback.
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* Fix bugs
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* Fix typo.
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* Fixed for lint
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* Follow review feedback to modify code.
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* Fix typo.
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* Port SP to Praxis
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* Fix an issue when enabling both GQA and RoPE.
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* Update docs
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Removed cudaMalloc/WorkspaceManager in JAX csrc. JAX custom ops now request buffers from XLA for their workspace tensors.
Signed-off-by: Alp Dener <adener@nvidia.com>

* removed unused GEMM C++ API in TE-JAX
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* fixed typo in layernorm_geglu_fp8_mlp and removed unnecessary shape reductions in primitives
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* fixed import order for linting
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* fixed custom op errors due to incorrect static arg nums in JAX jit
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* shifted cudnnSetStream further down the kernel to avoid error when executing dummy kernel call with nullptr stream
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* fixed linting errors for blank lines
Signed-off-by: Alp Dener <adener@nvidia.com>

---------
Signed-off-by: Alp Dener <adener@nvidia.com>

* Support num_gqa_groups arguments
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* Add GQA support on the JAX bridge code
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* Fix the kv stride of the arbitrary backend
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* Complete rewrite fused attention tests and add GQA coverage
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* Support unfused GQA
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* Calculate seqlen before the primitive for the better perf
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* Add GQA layer tests
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* Apply code style checks for te_jax
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* Apply code style checks for tests
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* Add num_gqa_groups doc
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* Refine the qkv_type
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* Correct the variable naming
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* Handle Max512 CAUSAL
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* Add WAR for the latest jax image
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---------
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Integrate cuDNN frontend v1 to fused attention and miscellaneous fixes
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* fix lint
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* fix jax/pytorch lint
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* simplify stride generation
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* fix and/or logic in get_backend
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* fix flag_max512 and test_numerics
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* remove v.contiguous() since get_qkv_layout covers it
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* skip fp8 tests for sm89
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* further fix jax CI
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* fix jax CI
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* revert mask type to comma-separated list
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* fix lint
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* fix last two commits
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* integrate v1/pre-release-5
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* cleanup prerelease5 integration and fix FA2.1 commit
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* force dropout to 0 if not training
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* fix Jax CI
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* testing bias/alibi and padding+causal; add alibi to unfused DPA
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* set flag_arb to false when non determinism is not allowed
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* followup on prev commit; remove redundant python env var setting
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* WIP: minor tweaks for tests
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* prepare for tests
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* fix determinism logic for fused attn
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* add bias to bwd
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* fix gpt_checkpointing/dpa_accuracy problem
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* fix some seg fault issues
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* add failure notes
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* remove use of non-deter var for backend selection
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* minor fix for lint and CI
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* fix workspace size in bwd and uncomment bias test
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* fix get_alibi and remove check_support
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* update tests status
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* remove workspace_opt from FADescriptor_v1
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* disable arbitrary backend + post scale bias in Jax; waiting on PR 525
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* clean up bhsd order
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* remove support for padding_causal + cross for max512
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* change alibi bias to float32 for bias_1_4/5 tests
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* further clean up tests
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* fix thd fwd output shape for FlashAttention and add backend info for DPA
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* fix definition of workspace limit when dbias is present
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* further tweak DP_WORKSPACE_LIMIT definition
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* disallow alibi+no_mask for sdpa flash and update alibi tests
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Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* disable dbias for non-hopper archs
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* remode unused arg for lint
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove build dir in setup.py
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* change selection logic to prefer fused attn on sm90
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* fix h and s order in header
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* remove manual setting of workopt path due to dbias after v1 update
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* add post_scale_bias and alibi to sdpa flash support matrix
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix support matrix in header files
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* move headers back to .cu and change seed/offset to int64
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* update Megatron commit in L1 test and remove all prints in fused attn test
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix L1 Megatron test
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix fp8 arg in L1 Megatron script
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* print only when debug flag is on
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove checkpointing loading to avoid loading other tests results
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

Support layernorm sm_margin through environment variables
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Do not include logging macros in installed C headers
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Debug C++ tests

Use Google style for header includes.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Update CUDA driver macros

Incorporating changes from #389.
Co-authored-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Jan Bielak <jbielak@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use core error checking macros in PyTorch extensions

Hack to get around macro redefinition warning.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix missing arg when getting CUDA driver error string
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Reuse logging header in frameworks
Signed-off-by: Tim Moon <tmoon@nvidia.com>

---------
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Jan Bielak <jbielak@nvidia.com>

* Fused attention kernel only supports sm80 and sm90
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update transformer_engine/jax/csrc/modules.cpp
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* arbitary fused kernel supports sm86/sm89 after 8.9.3
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Skip sm70
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Forward is_fused_attn_kernel_available to cpp backend
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Remove cpp is_fused_attn_available API
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Fix flash attention dropout probability with inference
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add output as the fused attention ctx tensor
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add rng_state as the fused attention ctx tensors
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add flash attention supported lengths to the fused attention
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refactor attention primitive to reuse abstract shaped array
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Detect backend type to allocate appropriate ctx size
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Skip dropout correctness instead of return success
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use cudaMemsetAsync and enhance the error handling
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add flash attention kernel elts_per_thread update
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Remove redundant max 512 suffix
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Keep only DType and remove NVTEDType from python
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix a float32_attention_logits bugs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Re-calculate workspace size for self attention
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance bias/dbias shape guard
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the seed/rng_state checker
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use jax.core.ShapedArray as jax.abstract_arrays is deprecated
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the unittest docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Add fused attention unit tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use NVTE_* enums
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use NVTE_Mask_Type and remove FMHADescriptor
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move common functions to utils
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change namespace to fused_attn
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move fused_attn_max_512_fwd_qkvpacked under the general APIs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add fused_attn_max_512_bwd_qkvpacked
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move fused_attn_max_512_bwd_qkvpacked under the general APIs
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Remove redundant blank line
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix a potential bug for cu_seqlen converter
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Reformat fused_attn_max_512
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refine the unfused attention warning message
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Rename to fused_attn_max_512
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Remove the deprecated header
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix flax import
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Rename to fused attn
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add attention related mask
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add attn_mask_type and attn_bias_type
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refactor jax primitive API
* Merge q_cu_seqlen and kv_cu_seqlen
* Remove is_causal_masking
* Replace seed with rng_state
* Add is_training argument
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Remove dsoftmax from the customcall
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add None guard for bias and dropout_rng
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add version guard
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add is_fused_attn_kernel_available() to correctly dispatch the attention impl
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix the merge conflict
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Adjust the code style
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add the missing blank lines
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change the order of FADescriptor members
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the readability of fused_attn_max_512.cu
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Generalize the input dimension unpacking
Signed-off-by: Reese Wang <rewang@nvidia.com>

* 16 bits fused attention requires 8.9.1
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update fused attention support matrix
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Handle None type when sharding
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change to the padding ratio
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Performance optimization for non-bias cases
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revert the cudnn-frontend PRIVATE keyword which was used for debugging
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revert "Update fused attention support matrix"

This reverts commit 4effe67d0f08f733919a329ce5ab421958740f4a.
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Treat b * s as total_seqs to align ragged cases
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add FP16/BF16 max_seqlen <= 512 fused attention to the support matrix
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refine test_fused_attn.py

* Replace reference code with flax.linen
* Remove unnecessary comments
* Use AttnMaskType
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Unify the cuDNN compile version
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add dropout to the support matrix
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Slightly adjust the headers
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Typo fix: remove redundant either
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Consolidating fused attention requirements
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Replace cudnn_frontend::throw_if with NVTE_CHECK for the better error line report
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Rename to fused_attn_fp16_bf16_max_seqlen_512 for the better readability
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Add more annotations to the custom calls
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Add zero_center_gamma/functional pass
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add zero_centered_gamma for fp8_ln_mlp
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add zero_centered_gamma to modules
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add zero_centered_gamma to TransformerLayer
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refactored code style for improved readability and consistency
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Docs enhancement for zero_centered_gamma
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add escape for line break and remove some bad if conditions
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revise scale_init docs
Signed-off-by: Reese Wang <rewang@nvidia.com>

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>

* add building workflow for jax modules
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* replace bit_cast with reinterpret_cast
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add nvtx to cmake check list
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor layernorm fwd
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor rmsnorm fwd
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor layernorm_bwd
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* set pytorch as default in setup.py
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* rename extension from *.cc to *.cpp

cpplint cannot recognize *.cc file, so rename the extension
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor style, to align TE/PyTorch
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add pybinding, unittest and qa
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix license
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* disable c-extension-no-member and no-name-in-module
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add dataclass avoid pylint error
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update transformer_engine/__init__.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update tests/jax/test_custom_call_shape.py

fix typo
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update tests/jax/test_custom_call_shape.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* add building workflow for jax modules
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* replace bit_cast with reinterpret_cast
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add nvtx to cmake check list
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor layernorm fwd
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor rmsnorm fwd
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor layernorm_bwd
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* set pytorch as default in setup.py
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* rename extension from *.cc to *.cpp

cpplint cannot recognize *.cc file, so rename the extension
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor style, to align TE/PyTorch
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add pybinding, unittest and qa
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix license
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* disable c-extension-no-member and no-name-in-module
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* add dataclass avoid pylint error
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update transformer_engine/__init__.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update tests/jax/test_custom_call_shape.py

fix typo
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update tests/jax/test_custom_call_shape.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* fix conflict due to PR62
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix c-extension-no-member and no-name-in-module

1. add transformer_engine_jax into extension-pkg-whitelist
2. convert pylintrc from CRLF to LF format
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update setup.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* remove pylint:disable and refactor import order
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

---------
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>