GitLab

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

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

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

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

Check input dimensions for SP
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

userbuffer pushsend/recv fix with atomicAdd_system
Signed-off-by: Sangkug Lym <slym@nvidia.com>
Co-authored-by: Sangkug Lym <slym@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>

* 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>

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

* refactor attention out of transformer.py
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

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

* ONNX export refactoring

* Remove infer_ort (to enable more testing)
* Add BF16 ORT tests for Q/DQ ops and GELU.
  * Use FP32 i/o instead of BF16 (because ORT doesn't support BF16 i/o) and add casts from FP32 to BF16 (this is only for subgraph inputs and outputs).
  * We'll need to add more BF16 testing.
* GEMM:
  * Add cast after DQ to achieve better performance (matmul at sub-fp32 precisions).
  * Fold bias into Gemm operation (=> smaller graphs)
  * Wrap GEMM-GELU with FP32 (TE implements GELU in FP32)
* Enable tests for cross attention (test_export_multihead_attention)
* Reduce test thresholds for test_export_layernorm_mlp, test_export_layernorm_linear, test_export_layernorm
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

* Loosen MHA export validation thresholds for FP16
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

---------
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

DDP support for no-bias option
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* move dbias from input list to output list for bwd
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* split asserts into three for bias checks
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

* another fix for asserts for bias checks
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>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>

* using different strems for pushsend and pushrecv
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* fix stream dependency
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* add wait from main_stream to memcpy stream
Signed-off-by: Sangkug Lym <slym@nvidia.com>

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

Use only built-ins for setup
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

Fixes in nested autocast
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* iFix LN ONNX export

When exporting LayerNorm make sure that the weights and bias
inputs have the same type as the LN input.
Also:
 * Add a regression test.
 * Add environment variable to override directory of generated test artifacts
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

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

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

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

Fix bug in Sequence Parallelism
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Adjust Module Structure.

1. Collect Flax related modules to a sub-folder, flax.
2. Add a function to unify scale_init for zero-centered-gamma LN.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Make changes be compatible to previous versions.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adapt jax/examples to the new module structure.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Update jax/docs and Add deprecated warning.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

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

* Adding deprecated warning to flax modules which imported via transformer_engine.jax
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix CI errors and update docs.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Removing unnecessary deprecated warning in docs.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Implementing __iter__ to DeprecatedEnum.
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: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Remove the nonexistent parameter from fused attention documentation
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Remove the second instance
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

* Faster split of QKV for FlashAttention
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

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

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

* Message with assert
Co-authored-by: Przemyslaw Tredak <ptredak@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

* make clarifying comment and check strides
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>

remove used function ternary_pw_op_create
Signed-off-by: Charlene Yang <charleney@nvidia.com>
Co-authored-by: Charlene Yang <charleney@nvidia.com>

add cast for BF16 input/output types for Q/DQ ONNX ops
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* Add FP8 fused attention to TE for PyTorch
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* add license for cudnn-frontend, modify installation requirements, and refactor some headers for aesthetics
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* add c api docs for fused attention
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* add exception for unsupported precision/sequence length combinations
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* fix installation requirement for non fused attn use cases
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* fix docs for fused-attn
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* prefix enums with NVTE_ and replace old MHA_Matrix with NVTE_QKV_Matrix
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* minor fixes based on PR comments
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* fix description for kvpacked fwd
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* fix description of Bias in C api
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* minor fixes for cudnn requirement and description for QKV tensors
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* fix QKV layout description and support matrix for C api
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* add asserts to cpp_extensions for qkv layout/bias type/attn mask type
Signed-off-by: Charlene Yang <charleney@nvidia.com>

* fix typo precision
Signed-off-by: Charlene Yang <charleney@nvidia.com>

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

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

* Fix linking issue and make mpi conditional
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Use max SMs at the last RS chunk in pipelined overlap
Co-authored-by: Sangkug Lym <slym@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Make userbuffers support opt-in

Decouple userbuffers from MPI. Refactor MPI handling in build system. Standardize names to "userbuffers".
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

---------
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Sangkug Lym <slym@nvidia.com>
Co-authored-by: Tim Moon <tmoon@nvidia.com>

* Allow update_collections and update_fp8_metas to return both Dict and FrozenDict.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Fix the wrong shape issue of bias when fused QKV or KV.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Reuse tuplized features for bias creating.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Replace get_args to be more readable.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* Port initial changes
Co-authored-by: Sangkug Lym <slym@nvidia.com>
Co-authored-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* readd FA include for PyTorch
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Re-enable sm_70 + cleanup
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* LICENSE, cleanup header
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* 5k -> 173 errors
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* license and fixes in userbuffers-host
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

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

* Turn off default async amax reduction (#148)
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* remove unused code path
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* cleanup Macros
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* fix conflict resolution bug
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* Fix gencode flags in setup (#145)

* Fix gencode flags based on cuda version
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

* Change overlap config dict error message
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* simplify ub initialization
Signed-off-by: Sangkug Lym <slym@nvidia.com>

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

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

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

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

* fix TE macros in public header
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* compiles with and w/o MPI
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* fixes for python side annotations for conditional compile
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* link gdrAPI only when MPI found
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* fix comments for dummy var
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

* load MPI before TE
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Add Py side argument checks
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* remove unused code and catch silent failures
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* fix find_lib path for tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

---------
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Sangkug Lym <slym@nvidia.com>
Co-authored-by: Sangkug Lym <slym@nvidia.com>
Co-authored-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* amax reduction internval
Signed-off-by: Sangkug Lym <slym@nvidia.com>

Skip TP-domain only AMAX reduction when TP-group is not initialized
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* Update transformer_engine/pytorch/fp8.py
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Sangkug Lym <slym@nvidia.com>

* check TP group initialized
Signed-off-by: Sangkug Lym <slym@nvidia.com>

fix
Signed-off-by: Sangkug Lym <slym@nvidia.com>

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

* use upstream flash-attn
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* get correct FA for linting
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>

* Fix model load exception when state resides on GPU

- Whenever converting a torch.tensor to numpy, we need to first
migrate the tensor storage to the host CPU.

- Add a warning not to do contant-folding when exporting to ONNX.
This is due to a torch.onnx export bug.

- Refactor compare_outputs
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

* Onnx export: Improve remark text
Signed-off-by: Neta Zmora <nzmora@nvidia.com>

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

Remove the autocast_variable
Signed-off-by: kaixih <kaixih@nvidia.com>

Fix cyclic import error in TF
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* made bias configurable
Signed-off-by: Naman Goyal <naman@fb.com>

* removed commented lines
Signed-off-by: Naman Goyal <naman@fb.com>

* Update transformer_engine/pytorch/jit.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: ngoyal2707 <ngoyal2707@users.noreply.github.com>

* Update transformer_engine/pytorch/jit.py
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Signed-off-by: ngoyal2707 <ngoyal2707@users.noreply.github.com>

* fixed incorrect call to fused bias dropout add kernel
Signed-off-by: Naman Goyal <naman@fb.com>

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

* Separate FC1 and FC2 use_bias args; solves all ci errors
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

---------
Signed-off-by: Naman Goyal <naman@fb.com>
Signed-off-by: ngoyal2707 <ngoyal2707@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: Naman Goyal <naman@fb.com>
Co-authored-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Rename enable_fp8 to is_fp8_enabled.
Signed-off-by: Ming Huang <mingh@nvidia.com>

* Adding an API to get an instance of  DelayedScaling which is set via fp8_autocast.
Signed-off-by: Ming Huang <mingh@nvidia.com>

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

* small cleanup before starting
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* conditional dgrad for Linear
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* add tests and small improvements to LNLinear and LNMLP
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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