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* First pass refactor
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* first pass
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* Change src file name in cmake
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* Move comments around
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---------
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* Move multi tensors kernels from PyTorch extensions to core
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* Add int16 type to core (for storing fp32 param remainders)
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* same fix to scale
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* Fix perf, memory, vars
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* Fix junk output dtype for non-per tensor
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* Fixes for test and upgrade mcore version
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* Fix core tests
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---------
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* Add GEMM logic for blockwise quantized tensors.

GEMM test cases included in pytorch integration.
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* Update NVTE_BLOCK_SCALING for GEMM.
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* Gate feature on CUDA 12.9
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* MR Feedback.
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* Run against tensor dumps from internal library.
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* Update FIXME to TODO with linked issue.
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* Update full recompute feature to save recipe.

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* MR Feedback. Avoid reusing quantizer objects.
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* Update usage method to satisfy upstream changes.
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* fix subchannel recipe in distributed test with bf16 gather
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* Edit and cleanup BF16 gather code.
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* support columnwise only mode to 1D quantize kernel
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* Add test for sanity and CG; fix CG for sequential?
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* Keep make_quantizers API stable

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* Fix import name.
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* refactor for nvte_quantize_v2
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* Test fp32 scales.
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* Simplify layernorm linear
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* LayerNorm linear bwd gather logic.
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* Communication updates.
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* Update transformer_engine/pytorch/ops/op.py

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* Lint fix.
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* Blockwise float8 quantizer and quantized tensor class.

The classes are configurable for 128x128 blocksize
and 1x128 blocksize via setting block_scaling_dim == 2,1 respectively.

Scale tensors are stored in a format emenable for matrix multiplication,
however the integration of matmul is deferred as a separate story.

Fusions of quantization and DBIAS or activation functions are not yet
implemented, and the dequantization is currently implemented in torch.

Tests for quantization are included in C++ and pytorch layers, with
exact comparison to reference quantizer behavior as well as an attempt
to hit interesting branches through the API such as tensor creation
in pytorch and CPP and dequantization of row and columnwise usage.

Two CUDA kernels for quantization are included, and are direct ports
of equivalents in the kitchen repository, where a subchannel recipe
has been used for end to end training.
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* Alignment for 1D scaling for GEMM edge case.
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* Tests for torch tensor API surface.

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* Reuse scale calculation between quantizer refs.
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---------
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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* add long sequence support and unify three backends for fused attention
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* update cudnn-frontend to v0.9.1
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* replace cpu_float2half_rn with __float2half_rn
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

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

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

* make cudnn plan caches thread_local
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

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

* replace cuDNN throw with NVTE_CHECK
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix replacement of cuDNN throw with NVTE_CHECK
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* force dropout probablity to 0 in inference mode
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* change negInfinity to be consistent with m512 fused attn
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove float2half conversion for scale_dropout
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add back runtime api for sm detection
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* add gemm3 to enums FP8Fwd/BwdTensors
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* change dropout from no to yes for fmha_v1
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove output_rng_state in m512 kernels
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* fix elts_per_thread calculation in kvpacked fwd
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove dropout=0.0 restriction for m512 fused attn
Signed-off-by: Charlene Yang <8636796+cyanguwa@users.noreply.github.com>

* remove output_rng_state completely from m512 kernels
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>

* Added ReLU and GLU variants to common
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

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

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

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

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

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

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

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

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

* Review comments
Co-authored-by: Przemyslaw Tredak <ptrendx@gmail.com>
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>

* 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>

* Add FP8 support for Ada
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

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

* better message for no fp8
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* same thing for onnx test
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

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

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

* Increase number of FP8 tensors per GEMM
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Enable FP8 output tensor for fp8_gemm
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* [BERT FP8] Initial TE review comments
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Temporary fix for cuda graph non convergence
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Address review comments-2
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Review comments-3
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Cleanup
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Change for New API
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Remove unnecessary clone for D_scale, D_amax
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Avoid Roll for AMAX history size = 1
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Update onnx_te_gemm API
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

* Fix Lint errors
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

---------
Signed-off-by: Vasudevan Rengasamy <vrengasamy@nvidia.com>

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

* Add ONNX export support for TE modules (#1)

* Add TorchScript Operators
* Add symbolic methods to ONNX exporter
* Add tests for the ONNX export
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* fixes for pylint tests
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* fix pylint warning in softmax.py
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* move FP8 ORT lib inside tests/
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* enable cross attention tests
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* refactor code by @nzmora
* Increase layernorm FP16 threshold
* Normalize onnx file names: _ separates configs; - separates words in a single config
* Add get_attn_mask_str and fix mask string
* Add missing ONNX files
* Moved generated ONNX files to tests/gen_onnx_models/
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* fix merge conflict changes
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* fix Q/DQ scale input
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* enable FP16 config when bias is disabled
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* fix pylint check errors
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* updates
1. remove List import for pylint failure
2. address comments: remove state tensors from GPU
3. address comments: Update reverse_map_dtype function and add to namespace
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* minor fix: coding guidelines
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* changes:
1. skip FP8 tests on  non-hopper devices
2. minor fix for C++ lint check
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* fix onnxruntime version
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* minor fix: add space between code and comment
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* changes
1. update copyrights
2. update path to ORT .so
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* Apply suggestions from code review
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: asfiyab-nvidia <117682710+asfiyab-nvidia@users.noreply.github.com>
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>
Signed-off-by: asfiyab-nvidia <117682710+asfiyab-nvidia@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* Move the amax/scale/scale_inv into the TE Tensor struct.
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

* Changed softmax to new Tensor
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

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

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

* Fix cast_to_fp8
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Przemyslaw Tredak <ptrendx@gmail.com>
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
Signed-off-by: Przemyslaw Tredak <ptrendx@gmail.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Make fused softmax kernels PyTorch independent
Co-authored-by: Sean Lee <selee@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

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

* move get_batch_per_block to python
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* fix license in softmax.h
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Co-authored-by: Sean Lee <selee@nvidia.com>

* Add kernel for multi-tensor cast-transpose
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix incorrect test function in multi-tensor cast-transpose unit test
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Remove std::vector from multi-tensor cast-transpose function signature

Makes sure the main header is C-compatible.
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Przemyslaw Tredak <ptredak@nvidia.com>

* Remove fp8_out from LN API
Signed-off-by: Przemyslaw Tredak <ptredak@nvidia.com>

* fix LN test
Signed-off-by: Przemyslaw Tredak <ptredak@nvidia.com>

* Fixes
Signed-off-by: Przemyslaw Tredak <ptredak@nvidia.com>
Signed-off-by: Przemyslaw Tredak <ptredak@nvidia.com>
Co-authored-by: ksivamani <ksivamani@nvidia.com>

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