GitLab

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

* Add GQA support on the JAX bridge code
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix the kv stride of the arbitrary backend
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Complete rewrite fused attention tests and add GQA coverage
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Calculate seqlen before the primitive for the better perf
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Apply code style checks for te_jax
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Apply code style checks for tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

* Correct the variable naming
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Handle Max512 CAUSAL
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add WAR for the latest jax image
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

* Applying cast to the kernel of layernorm_fp8_dot
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Applying native cast to the kernel of fp8_dot.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Apply Cast and native cast to layernorm_geglu_fp8_dot
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix the bug to enable layernorm_geglu_fp8_dot in LayernormMlp
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Modifiied code with the review feedback.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding 2xACC control to FP8 GEMMs.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Set precision as an static arg
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

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

applied Google-advised fix to register custom op primitives with the device dispatch list
Signed-off-by: Alp Dener <adener@nvidia.com>

* Integrate cuDNN frontend v1 to fused attention and miscellaneous fixes
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* fix jax/paddle for unit tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

* fix and/or logic in get_backend
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix flag_max512 and test_numerics
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove v.contiguous() since get_qkv_layout covers it
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* skip fp8 tests for sm89
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

* revert mask type to comma-separated list
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

* integrate v1/pre-release-5
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* cleanup prerelease5 integration and fix FA2.1 commit
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* force dropout to 0 if not training
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* testing bias/alibi and padding+causal; add alibi to unfused DPA
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* set flag_arb to false when non determinism is not allowed
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* followup on prev commit; remove redundant python env var setting
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

* fix determinism logic for fused attn
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* fix gpt_checkpointing/dpa_accuracy problem
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix some seg fault issues
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* remove use of non-deter var for backend selection
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* fix workspace size in bwd and uncomment bias test
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix get_alibi and remove check_support
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* remove workspace_opt from FADescriptor_v1
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* disable arbitrary backend + post scale bias in Jax; waiting on PR 525
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* clean up bhsd order
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* swap bias/rng_state order in aux_ctx_tensor and add bias to aux_ctx_tensor in _qkvpacked/_kvpacked API
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove support for padding_causal + cross for max512
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* change alibi bias to float32 for bias_1_4/5 tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* further clean up tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix thd fwd output shape for FlashAttention and add backend info for DPA
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix definition of workspace limit when dbias is present
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* further tweak DP_WORKSPACE_LIMIT definition
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* disallow alibi+no_mask for sdpa flash and update alibi tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* update jax/paddle after PR525 and fix DP_WORKSPACE_LIMIT for dbias Jax tests
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>

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

* Add rng_state output for cross fused attention
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add rng_state and output for the flash attention backward
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add bias for the jax cross attn API
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Add bias in the backward for the arbitrary fused attn backend
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

Use relative idx to ScaledUpperTriangMaskedSoftmaxFwdPrimitive.abstract to support batching.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* Fix JAX distributed unit tests name
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Refactor sharding.py for the further custom_partitioning migration
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Migrating both FWD and BWD of LayerNorm/RMSNorm from xmap to custom_partitioning.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Migrating both FWD and BWD of all kinds of softmax from xmap to custom_partitioning.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fix the wrong order of parameters to LN/RMSN bwd in ln_mlp_fp8.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* WAR to LN/RMSN_fp8 before migrating to CP.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fix the wrong order of parameters of bwd of LN/RMSN_fp8.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Following review feedback to modify
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Force the hidden dim in Norm ops to no sharding and add warning msg.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Reuse fwd_rule in VJP functions
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Migrating both FWD and BWD of self-fused-attn from xmap to custom_partitioning.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Migrating both FWD and BWD of cross-fused-attn from xmap to custom_partitioning.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* add gelu and dgelu.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Reuse fwd_rule in VJP functions for attentions
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Apply native FP8 Dtypes to fp8.py
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Migrating cast_and_transpose from xmap to custom_partitioning
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Migrating transpose from xmap to custom_partitioning
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Apply XLA pattern match to perform FP8 GEMM.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* migrate layernorm_fp8 to custom_partitioning.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Unify code style
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Extend supported of Transpose with FP8
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Implementing layernorm_fp8_dot based on migrated custom calls.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Renaming variables and publish NVTE_FP8_COLLECTION_NAME
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Replace Q/DQ custom calls with native XLA implementations
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* migrate gelu_fp to custom_partitioning.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

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

* Support custom calls with mutli-dims
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Support gerneral dot indices in _fp8_dot_impl
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Implementing layernrom_geglu_fp8_mlp
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Remove GEMM custom calls
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Remove xmap related code
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fix typo and add query-function to FP8MetaPackage
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fix some bugs of custom calls
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fix CT's bugs
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Update UTs/eaxmaples to adapt to the API changes.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Unify kernel initilization in MLP.
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Modifing with code review's feedback
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Update README and Add deprecating warning to *ShardingType
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Canonicalize the dtype
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding assertion for non-supported batch dims.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding doc/examples to _multidim_transpose
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Set FP8 meta as WeightHParamsCollection.OVERWRITE_WITH_GRADIENT in Praxis modules.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Set FP8 meta as WeightHParamsCollection.OVERWRITE_WITH_GRADIENT in Praxis modules.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Apply dtype-based rtol/atol to UTs
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Deprecate QKV_INTERLEAVED enum
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Skip test_distributed_custom_ops.py
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix the wrong sharding of bias in SelfAttn
Signed-off-by: Ming Huang <mingh@nvidia.com>

* WAR to fix the wrong cu_seqlen of MHA when DP/FSDP enabled
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding distributed ops unit-tests
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* Follow review feedback to modify
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Use total bytes involved in collective ops as criteria.
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>
Co-authored-by: Donglin Yang <dongliny@nvidia.com>

[C/JAX] Support more mask types for the arbitrary seqlen kernels and minor changes of JAX bias (#469)

* Move bias to float32
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Increase neg infinity abs values
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

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

* Support variable sequence length after cuDNN 8.9.6
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Use unique_ptr instead of shared_ptr
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add a new mask type: PADDING_CAUSAL_MASK
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Support flash padding mask after 8.9.6
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the Max512 handling for causal masking and add the related tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update the fused attn support lists
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

* Reduce the pad ratio tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix a bug with cuDNN 8.9.5
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Release backend resource after the module level unit test
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Clean the jax live arrays before running the unit tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

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

* Deprecate QKV_INTERLEAVED use in JAX
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Deprecate QKV_INTERLEAVED use in Paddle
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance qkv enum mappings
Signed-off-by: rewang <rewang@nvidia.com>

* Fix LD_LIBRARY_PATH issue
Signed-off-by: rewang <rewang@nvidia.com>

* Arbitrary seqlen kernels only support self attention currently
Signed-off-by: rewang <rewang@nvidia.com>

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

fixed incorrect of extend_fsdp_sharding_meta() in cross_fused_attn()
Signed-off-by: Alp Dener <adener@nvidia.com>

canonicalize the dtype for the better user experience
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* [JAX] Enhance Dropout in TransformerLayer.

1. Fixed missing setup of dropout RNG key in TransformerLayer and
   LayerNormMLP.
2. Allowing seperated dropout rate for FC1's output and other hiddens.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix wrong fp8 scale in _update_fp8_metas_impl
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

Change deprecation warnings
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@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>

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

Use the new API when it is available.
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

* [JAX] Fix incorrect sharding when only enable FSDP.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* [JAX] Add WAR to memory misaligned issues of LN BWD.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* [JAX] Reuse sm_arch for avoiding duplicate code.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* [JAX] Support multiple sizes allocation in WorkspaceManager.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* [JAX] Use template and ariadic arguments to improve multple sizes allocator.
Signed-off-by: Ming Huang <mingh@nvidia.com>

---------
Signed-off-by: Ming Huang <mingh@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>

* Initially commit for FSDP
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding support to fsdp xmap sharding
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Specify WeightHParamsCollection of fp8 meta.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Support partial FP8 custom calls with FSDP.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding amax reduction on the fsdp mesh dim.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* Fix the wrong batch axis in logic_axis_rules and add sharding_constraint to BMM1
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Support FSDP in fMHA.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix missing all-reduce of wgrads along FSDP axis.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Change default value of fsdp_axis_name to  for aligning with others
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix RuntimeError: with_sharding_constraint requires a non-empty
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Slightly changes (review feedback)
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Removed unnecessary comments
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Mergeing input_dp_dim into weight_fsdp_dim_map
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.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>

* Fully remove attn_type and set self_attn_mask_type default to 'causal'
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix tests with new arguments
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Explicit self_attn_mask_type for examples
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update transformer_engine/jax/flax/transformer.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: zlsh80826 <rewang@nvidia.com>

* Update transformer_engine/jax/flax/transformer.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: zlsh80826 <rewang@nvidia.com>

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Signed-off-by: zlsh80826 <rewang@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* Cast the uint32 key/counter to int64
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Revise devPtrCuSeqlen* to align the naming
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Support different Jax PRNG impls
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Revert CastAsync since it is not used
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Implement is_training for 16-bit fused attn
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add fused attn with dropout sanity unit tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Enhance the comments readability and rng_state checker
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change the attention dropout shape to align other frameworks
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Make encoder tests deterministic
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Change the default seed for the jax encoder tests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Maintain offset in TE
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Revert rng_state type to allow only i64
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Handle the corner case for elts_per_threads calculation
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Populate rng state by kernels
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Rename rng_state as seed in cpp_extensions
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update the attention dropout comment
Signed-off-by: Reese Wang <rewang@nvidia.com>

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Add self_attn_mask_type and replace attn_type
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refine the keyword style for the better readability
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Replace attn_type with attn_mask_type in praxis transformer
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

---------
Signed-off-by: Reese Wang <rewang@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Use the same default in the function to what the class default.
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

* Assert instead of silently ignoring not supported variation. Small doc correction, amax_compute_algo is partially supported.
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

* Fix line lenght to fix the CI.
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

* Apply suggestions from code review
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Frédéric Bastien <frederic.bastien@gmail.com>

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

* Clarify that it is only TE/JAX that don't support that faeture.
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

* Update transformer_engine/jax/fp8.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Frédéric Bastien <frederic.bastien@gmail.com>

* Update the test following the change in default value
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

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

---------
Signed-off-by: Frederic Bastien <fbastien@nvidia.com>
Signed-off-by: Frédéric Bastien <frederic.bastien@gmail.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Ignore IDE files
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Fix typing errors
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Ignore devcontainer files
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Avoid import from private module
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Apply @timmoon10 's suggestions
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

---------
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Refactor Setuptools build system

Successfully launches CMake install, but installs CMake extensions in temp dir.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug JAX build

Fix pybind11 import. Distinguish between build-time and run-time dependencies.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add helper function to determine dependencies
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add missing license
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug case where system CMake is too old
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add missing license
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Simplify sanity import tests

Just importing modules provides richer error messages.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Properly install submodules
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Install helper library for TensorFlow
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Do not install Ninja by default
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Include Git commit hash in version string
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Override build_ext.build_extensions instead of build_ext.run
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix incorrect include path

Restore Ninja dependency. Restore overriding build_ext.run func.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Review suggestions from @nouiz
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Disable parallel Ninja jobs in GitHub actions
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Properly install userbuffers lib
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Tweak install docs

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

* Add examples for specifying framework in docs
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Unfused scale+softmax if bias is present
Signed-off-by: Reese Wang <rewang@nvidia.com>

* WAR a causal masking + no_bias bug and add the unittests
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix the optional args (bias) sharding
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Disable fused attn in JAX by default, enable it with NVTE_USE_FUSED_ATTN
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add thread local for the plan cache
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

* Add scaled softmax with dropout test cases
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Updated NVTE_FUSED_ATTN variable name
Signed-off-by: Reese Wang <rewang@nvidia.com>

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

Signed-off-by: Frederic Bastien <fbastien@nvidia.com>

* Adding JAX/Praxis modules and dependencies.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding UTs to JAX/Praxis modules.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Remove praxis as a dependency due to not strictly needed
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Repalce is_fp8_supported to is_fp8_available
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Make Praxis as an optional dependency.

1. Removed 'from . import praxis' in __init__.py.
    1.1 Noted, keep 'from . import flax' for deprecated warning.
2. Changed te.flax to te_flax in examples and README.rst.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding a workaround to FP8 training on Praxis.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

bugfix for softmax lowering
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

[JAX] Fix missing axes parameters in TransformerLayer and the wrong shape of bias in LayerNormMLP (#196)

Fixed missing axes and wrong shape of bias in LayerNormMLP
Signed-off-by: Ming Huang <mingh@nvidia.com>

* add mp example
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

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

* update doc-string
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* better FP8 checker
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* update readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* replace te.* with te.flax* to remove deprecated warning
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove nouse os.environ
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove nouse
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

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

* Update examples/jax/encoder/README.md
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/test_multiprocessing_encoder.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove cuda-python
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* adjust readme
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Update examples/jax/encoder/README.md
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix cpp lint

fix issue of "Could not find a newline character at the end of the file."
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix AssertionError: 1 GPU per process
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* replace tfds with datasets

The Flax application crash if it use TensorFlow Dataset (tfds) in NVIDIA JAX container.
The tfds is very useful for downloading well-knwon dataset (e.g., MNIST, GLUE) and commonly used by TF/JAX community.
However, it seems like that it is NOT compatible with NVIDIA TensorFlow in NVIDIA JAX container and somehow affects JAX.
It triggers random errors at JAX initialization depending on different versions, and make CI unstable.
Thus, this commit replaces tfds with "huggingface datasets" to download needed datasets.
See "nvbugs 4039266" for more details.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix input sharding

Unlike SPMD mode, in multiprocessing mode, the input tensor must be sharded manually.
Using DP=4, TP=2 as an example, the device mesh looks like:

mesh.device_ids = [[0, 1],
                   [2, 3],
                   [4, 5],
                   [6, 7]]

Assume that the process ID is mapped to GPU ID.
The process 0 and process 1 are grouped for model parallelism,
process 2 and process 3 are grouped together too, and so on.

The process 0 and process 1 need to share the same micro-batch in the training step,
process 0 and process 2, 4, and 6 have different micro-batch.

Thus, `shard_array_wrapper` partitions inputs to 4 parts (and setup
needed arguments for jax.make_array_from_single_device_arrays).
The process 0 and process 1 take the first quarter,
process 2 and process 3 take the second quarter, and so on.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor UT for multiprocess example

Use Python `multiprocessing` to test the multiprocessing example,
if the system has multiple GPU. 1 GPU per process.

Because `jax.distributed.initialize` must be called before any other JAX or Flax API,
GPU info cannot be queried by calling jax.local_devices() in TestEncoder.
Thus, `unittest_query_gpu()` forks another process to query number of GPUs and
FP8 capability.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove nouse arg `--num-gpu`

JAX doesn't have an API to setup number of GPU used in SPMD mode.
The only way is to use `CUDA_VISIBLE_DEVICES` for now.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

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

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

* simplify the mask setting
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* increase batch-size for multigpu example

The batch-size 64 is too small to be partitioned for 8xH100.
If batch-size is 64, the GEMM shape is 256x8192x8 per GPU.
The 8 is too small for FP8 GEMM kernel, and
cuBLASLt will throw "Failed to query heuristics".
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* fix downloading mnist error

To download MNIST via `huggingface datasets`, it requires Pillow.
Otherwise, it throws `An error occurred while generating the
dataset`
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>
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.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>