GitLab

fix rng_state issue and minor compiler warning
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

Catch misaligned address errors
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* Expose MultiheadAttention for import
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Expand mask type and add no mask numerical test
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

Signed-off-by: Sudhakar Singh <sudhakars@nvidia.com>

* Add nn.layer: softmax, attention, transformer
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

* code refactor
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

* code refactor
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

* update docs and set dropout=0.1
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

* Update transformer_engine/paddle/layer/attention.py
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

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

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

* Change API and add to RMSNorm
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

* Save full global state
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* More fixes to test
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* add back pytorch csrc extensions.h
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* remove seqlen%32/64 checks for now
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* add tests for changes regarding rng_state in aux_ctx_tensor
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* reuse rng tracker from numerics in fused attn; skip checkpointing if FAv2 in numerics
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* uncomment comments used for testing
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix pre/post scale bias
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* Update transformer_engine/pytorch/attention.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: cyanguwa <8636796+cyanguwa@users.noreply.github.com>

* remove skipifs for FAv2 check after PR366
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove checkpointing tests for transformer layer; dpa tests still provide coverage
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* Add upper bound to FA version
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Check backend only when using FusedAttention
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* remove imports/variables related to FAv2 checks
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* further fix random number ranges for tests
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix variable referenced before assignment error
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>
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>

* Add dynamically shaped input mask in test_export_softmax
* Fix test_softmax_mask_fn - use env. var `NVTE_ONNX_KVCACHE_MAX_SEQ_LEN` to control whether the test uses the default mask generation function or dynamic TRILU mask slicing.
* Change core_attention ONNX export test: use "no_mask" as attn mask type when testing `te.attention.DotProductAttention` w/o masking.
* Use ORT CUDA backend by default.
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

* Add support for cuDNN fprop and FAv2 bprop
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* skip activation recompute tests if FAv2
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* restrict the use of FAv2 bprop to H100 only
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* move use_FAv2_bwd check to init
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove skipifs for FAv2 in test numerics
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix typos and wording for deterministic checks
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* Remove variables related to FAv2 skipifs
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: cyanguwa <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>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* fix linear sequence parallel when weight is frozen
Signed-off-by: jasonwan <jasonwan@nvidia.com>

* Extend fix to all APIs
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Disable FAv2 for deterministic use
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Also disable FusedAttention backend with deterministic
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* Optimize calls to .cpu() during checkpointing
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

Fix for the RMSNorm tests/doc/ONNX export to match the actual
implementation
Signed-off-by: Przemek Tredak <ptredak@nvidia.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>

* Cast Flax collections to FrozenDict as WAR to adapt Flax 0.7.1.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding min version of flax to requirements.txt in examples
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix praxis tests and rename compare_frozen_dict to compare_dict
Signed-off-by: Ming Huang <mingh@nvidia.com>

* [Paddle] Refactor FP8 state (#350)

Refactor fp8 state
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Store FP8 checkpointing data in CPU (#351)
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Make test_layer be able to run on both Flax >=0.7.1 and <=0.7.0
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

---------
Signed-off-by: Ming Huang <mingh@nvidia.com>
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Tian Zheng <tizheng@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Tim Moon <tmoon@nvidia.com>

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

Refactor fp8 state
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add FP8 support

- Add FP8 recipe
- Add FP8 path for nn layers
- Add MNIST FP8 example
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Update README
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix LayerNormMLP FP8 backward
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix FP8 training in float32 accumulation
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix FP8 checkpointing for non forward execution cases (same as #323)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Refactors and improvements for better code stype, readability and organization
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Remove unnecassary pylint override
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

---------
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

Add compilation warning for FA 2.0
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* add support for multi-query/grouped-query attention
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* revert to flash-attn 1.0.6 and build 2.0.0.post1 manually in CI
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add keyword name for DPA input
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

* Update transformer_engine/pytorch/attention.py
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Update tests/pytorch/test_fused_attn.py
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix TP and SP case
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* remove higher limit for flash-attn version
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: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Exposing RMSNorm in pyTorch extensions
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* First pass at the Python API
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

* Added numerics tests and fixed issues
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

* Added RMSNorm to LayerNormMLP
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Added ONNX export and tests for RMSNorm
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Fix python lint
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Fix BERT case
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Added normalization option to the TransformerLayer
Added tests
Fixed test failures
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Fix documentation
Co-authored-by: Przemyslaw Tredak <ptrendx@gmail.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Fix IMA and invalid type error
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Increase RMSNorm threshold for bf16 case
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

---------
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

Build PyTorch with FA for memory usage
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* add flash attn tests
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

* update flash attn
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

* fix random seed
Signed-off-by: Shijie Wang <jaywan@nvidia.com>

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

Replace deprecated sharding API
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Add Linear layer (FP16)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

- Add BF16 training example
- Add fp8_autocast (only supports non-fp8 for now)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Remove FP8 stuff
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Simplify Linear layer forward
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add LayerNorm layer (BF16)
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add LayerNormLinear layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Store weights in BF16
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add LayerNormMLP layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add BF16 MNIST example
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Remove in-place cast for compatibility with Paddle AMP mechanism
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* README correction
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Add Paddle op as a backend option
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix code format
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Fix dtype change between iterations
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Minor fixes
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Move forward function out of base layer
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* Use Paddle nvtx bindings
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

---------
Signed-off-by: Tian Zheng (Engrg-Hardware 1) <tizheng@nvidia.com>

* FA v2.0 support
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

* FA does not support head_dim > 64 on Ada
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Add cc8.7 to no FA list
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* layer number bug fixes
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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