GitLab

Delay MeshResource validation until first usage
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>
Co-authored-by: Phuong Nguyen <phuonguyen@nvidia.com>

* clean up sharding
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

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

* rework test for MeshResource
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* add mesh_resource into fp8_autocast in test_helper.py
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

[JAX] Error checking for mesh resource and update GemmPrimitive to use global_mesh_resource().fsdp_resource (#2088)

* Enforce global MeshResource is set
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Use global_mesh_resource().fsdp_resource in gemm primitive
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Update tests
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Update gemm.py
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Update test_layer.py
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

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Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* fix pspec check
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

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



* cleaning
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* add docstring
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* use dict.get()
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* fix lint
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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* add manual axis filer to sharding_constraint impl
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

* use abstract_mesh instead of physical_mesh
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* add a comment
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

* clean unused var
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

* rm batch_dim, sequence_dim, sequence_parallel_output
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* rm lhs_quantized_colwise and rhs_quantized_colwise
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* rm unnecessary transpose_batch_sequence arg from some modules
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Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

* remove dot1_output_axes
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

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

[JAX] Fixing GemmPrimitive partitioning rules to handle tensor-parallelism correctly for sequence-parallel inputs (#1980)

* updated GemmPrimitive partitioning rules to explicitly control all-reduce vs. reduce-scatter for sequence-parallelism
Signed-off-by: Alp Dener <adener@nvidia.com>

* corrected handling of FSDP sharding for the RHS operand
Signed-off-by: Alp Dener <adener@nvidia.com>

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



* use correct logical axes variable to identify sequence-parallel dim in LayerNormDenseGeneral
Signed-off-by: Alp Dener <adener@nvidia.com>

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

* added assert on sequence-parallel options when GemmPrimitive is disabled
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* Support flax sharding constraints
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Add warning for deprecated TE logical axes
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Update examples
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

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Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Support SWA in CP Ring Attn THD striped sharding
Signed-off-by: Hua Huang <huah@nvidia.com>

* Add some comments; move check to _FusedAttnCPWithP2PHelper.check_supported()
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



Remove unused check
Signed-off-by: Hua Huang <huah@nvidia.com>

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

* [JAX] Update flax module param initialization to support logical partitioning axes
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Fix ffn1 intermediate result being replicated
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* Lint
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Add documentation and assert when logical_axes=None
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Fix bias in LayerNormMLP flax module
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Fix layer tests to not use nn_partitioning and instead use nn.with_logical_axes
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

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Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* rename QuantizeAxis to QuantizeLayout, get_layout to get_data_layout, q_axis to q_layout

* add fatten_axis option

* added gated act to test encoder

* sharding constraint fixes

* fix padding when flattening first dim needs to be padded

* update test sizes so that padding is tested

* rm output sharding as it can be done in the flax module

* sharding scale_inv for mxfp8

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

* refactor + mxfp8

* added grouped gemm

* rename linear to dense

* added cublas init phase for groupedGemm

* relax the tol of test encoder multiprocessing mxfp8 by 0.001
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>

---------
Signed-off-by: Phuong Nguyen <phuonguyen@nvidia.com>
Co-authored-by: Hua Huang <huah@nvidia.com>
Co-authored-by: Jeremy Berchtold <jberchtold@nvidia.com>

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

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

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

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

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

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

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

* Refactor sharding.py for the further custom_partitioning migration
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* Migrating both FWD and BWD of LayerNorm/RMSNorm from xmap to custom_partitioning.
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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.
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* Following review feedback to modify
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* Force the hidden dim in Norm ops to no sharding and add warning msg.
Signed-off-by: Ming Huang <mingh@nvidia.com>
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* Reuse fwd_rule in VJP functions
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* Migrating both FWD and BWD of self-fused-attn from xmap to custom_partitioning.
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* 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.
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* Reuse fwd_rule in VJP functions for attentions
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* Apply native FP8 Dtypes to fp8.py
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* Migrating cast_and_transpose from xmap to custom_partitioning
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* Migrating transpose from xmap to custom_partitioning
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* Apply XLA pattern match to perform FP8 GEMM.
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* migrate layernorm_fp8 to custom_partitioning.
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* Unify code style
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* Extend supported of Transpose with FP8
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* Implementing layernorm_fp8_dot based on migrated custom calls.
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* Renaming variables and publish NVTE_FP8_COLLECTION_NAME
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* Replace Q/DQ custom calls with native XLA implementations
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* migrate gelu_fp to custom_partitioning.
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* Miner fix
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* Support custom calls with mutli-dims
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* Support gerneral dot indices in _fp8_dot_impl
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* Implementing layernrom_geglu_fp8_mlp
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* Remove GEMM custom calls
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* Remove xmap related code
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* Fix typo and add query-function to FP8MetaPackage
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* Fix some bugs of custom calls
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* Fix CT's bugs
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* Update UTs/eaxmaples to adapt to the API changes.
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* Unify kernel initilization in MLP.
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* Modifing with code review's feedback
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* Update README and Add deprecating warning to *ShardingType
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* Canonicalize the dtype
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* Adding assertion for non-supported batch dims.
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* Adding doc/examples to _multidim_transpose
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* Set FP8 meta as WeightHParamsCollection.OVERWRITE_WITH_GRADIENT in Praxis modules.
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* Set FP8 meta as WeightHParamsCollection.OVERWRITE_WITH_GRADIENT in Praxis modules.
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* Apply dtype-based rtol/atol to UTs
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* Deprecate QKV_INTERLEAVED enum
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* Skip test_distributed_custom_ops.py
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* Fix the wrong sharding of bias in SelfAttn
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* WAR to fix the wrong cu_seqlen of MHA when DP/FSDP enabled
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* Adding distributed ops unit-tests
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* Adding license to test_distributed_*
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* Follow review feedback to modify
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* Use total bytes involved in collective ops as criteria.
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---------
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>

* [JAX] Fix incorrect sharding when only enable FSDP.
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* [JAX] Add WAR to memory misaligned issues of LN BWD.
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* [JAX] Reuse sm_arch for avoiding duplicate code.
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* [JAX] Support multiple sizes allocation in WorkspaceManager.
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* [JAX] Use template and ariadic arguments to improve multple sizes allocator.
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---------
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* Adding support to fsdp xmap sharding
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* Specify WeightHParamsCollection of fp8 meta.
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* Support partial FP8 custom calls with FSDP.
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* Adding amax reduction on the fsdp mesh dim.
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* clean code
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* Fix the wrong batch axis in logic_axis_rules and add sharding_constraint to BMM1
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* Support FSDP in fMHA.
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* Fix missing all-reduce of wgrads along FSDP axis.
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* Change default value of fsdp_axis_name to  for aligning with others
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* Fix RuntimeError: with_sharding_constraint requires a non-empty
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* Slightly changes (review feedback)
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* Removed unnecessary comments
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* Mergeing input_dp_dim into weight_fsdp_dim_map
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* Update transformer_engine/jax/sharding.py
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---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
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* Unfused scale+softmax if bias is present
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* WAR a causal masking + no_bias bug and add the unittests
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* Fix the optional args (bias) sharding
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* Disable fused attn in JAX by default, enable it with NVTE_USE_FUSED_ATTN
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* Add thread local for the plan cache
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* Rename dbeta to dbias for the readability
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* Add scaled softmax with dropout test cases
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* Updated NVTE_FUSED_ATTN variable name
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---------
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add fused attention unit tests
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* Use NVTE_* enums
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* Use NVTE_Mask_Type and remove FMHADescriptor
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* Remove redundant blank line
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* Fix a potential bug for cu_seqlen converter
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* Rename to fused_attn_max_512
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* Fix flax import
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* Add attn_mask_type and attn_bias_type
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* Refactor jax primitive API
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* Remove dsoftmax from the customcall
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* 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>

* Updated TE/JAX docs
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding TE/JAX docs' rst files
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Set DType as pybind11::module_local() to avoid generic_type errors.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Updating license and exporting more modules
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adopting autoapi and removing enum_tools.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* Make jax.rst be style consistent.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fixing doc statements as the suggestion from review.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Fixing doc statements as the suggestion from code review.
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Update the description of Softmax
Signed-off-by: Ming-Xu Huang <mingh@nvidia.com>

* Removed categories in catalog as PyTorch
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>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* add transformer module , unittests and examples
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

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

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

* remove pylint: disable=line-too-long
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove pylint: disable=too-many-func-args
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Fix the wrong broadcasting dim to dropout masks when enable transpose_bs.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Enable 2xACC for WGRAD and DGRAD by default
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* rename LayerNormMlpBlock as LayerNormMLP
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* refactor to avoid line-too-long
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* rename amax_history_size to amax_history_len
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* align dropout mask to TE/PyTorch as default
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* enlarge atol for decoder unittests

Two decoder unittests can pass in old JAX container(e.g., 23.02)
but can't in latest container (devel).

1. The actual(-0.020264) and desired(-0.020386) are very close.
2. The TE kernels are not changed, the diff should come from
   new codegen behavior of XLA.

Thus, it is a common floating-point accumulated error.
Enlarge atol to avoid unittest failures.
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* Adding Amax History Support

1. hide amax update in custom_vjp
2. replace amax indexing with roll(using circular buffer)
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* move kernel_init to __post_init__
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

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

* Update transformer_engine/jax/fp8.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* Update transformer_engine/jax/fp8.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Jeng Bai-Cheng <jeng1220@users.noreply.github.com>

* remove envvar regarding 2xACC
Signed-off-by: Ryan Jeng <rjeng@nvidia.com>

* remove unused import
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: Ming-Xu Huang <mingh@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.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>