Commits · 71971e33dc01a015c943c8c3b73800eb047b8a78 · OpenDAS / TransformerEngine

"...git@developer.sourcefind.cn:OpenDAS/TransformerEngine.git" did not exist on "f8693d2b044ab83624e020ffa69f3412a916993d"

17 Jan, 2026 1 commit

Add logic for block-scaled tensors with GEMM swizzled scales (#2486) · 99df8810

Tim Moon authored Jan 16, 2026



* Add general C API for setting tensor params
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Implement general accessors for NVTETensor
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Refactor tex swizzling to skip if scales are already swizzled
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add checks for non-swizzled scales in MXFP8 and NVFP4 kernels
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Support pre-swizzled scales in MXFP8Tensor
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add tex function to swizzle MXFP8 scales
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix bug in inplace swizzle function
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Tweak comments to use "compact/swizzled format"
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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* MXFP8 quantize kernel with pre-swizzled scales
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Expose pre-swizzled scales in modules
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix bug in multi-swizzle
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Support MXFP8 gated activations with swizzled scales
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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* Add PyTorch infrastructure for pre-swizzled NVFP4 tensors
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* Deprecate DSv3-specific quantization logic in C API
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* Remove support for DSv3 compact data from quantizer
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* Remove DSv3 compact data format from core lib
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* Fix bug in FP8 all-gather
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* Fix linter warnings
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* Update JAX to use new swizzled scale API
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* Review suggestion from @greptile-apps
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* Review suggestions from @greptile-apps
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* Update C++ swizzle test with swizzled scales API
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* Return default tensor params when querying params for invalid NVTETensor
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* Debug DSv3 FP8 test failures
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* Debug Userbuffers test failures
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* Make sure gated activations populate FP8 transpose if needed
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* Review suggestions from @greptile-apps
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* Disable pre-swizzling with debug quantizer
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* Fix merge conflicts and review suggestions

Update copyright years. Tweak comments. Fix various complaints from @greptile-apps.
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* Use explicitly sized types in config accessors

Miscellaneous review suggestions from @ptrendx.
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* Make util header for function that compute swizzled scale index
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* Update expected error message in FP8 block-scaling test
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99df8810

02 Jan, 2026 1 commit
- Update copyright to include year 2026 (#2553) · 830ef60f
  Kirthi Shankar Sivamani authored Jan 02, 2026
```
Update copyright to include 2026
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
```
  830ef60f
20 Dec, 2025 1 commit

[PyTorch][NVFP4][MOE] NVFP4 Grouped Quantize with Hadamard Transform (#2411) · eb8e792b

Zhongbo Zhu authored Dec 20, 2025



* rowwise colwise RHT group quant v1
Signed-off-by: Zhongbo Zhu <zhongboz@nvidia.com>

* remove local array RW
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* change wait_barrier
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* fast math options
Signed-off-by: Zhongbo Zhu <zhongboz@nvidia.com>

* use mult to replace div
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* format
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* bulk move random states
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* greptile
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* lint
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* revert to use divides
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* avoid fp32 bf16 round-trip in RHT cast fusion
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* trigger fastmath by toggle NVTE_RHT_CAST_FUSION_USE_FAST_MATH
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* integrate row col rht fusion, functional
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* numerics aligned
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* style
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* remove device sync
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* 128 padding
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* revert colwise rng state creation because of row-col fused kernel
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* fix CI, linter
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* refactor RS for generating two random values
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* Avoid invalid configs with templated kernel
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* fix acc pipeline init with 0 arrival count
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* restore rowwise-only mode
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* switch to dynamic atomic scheduler
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* Avoid instantiating group RHT+cast kernel without row-wise or col-wise output
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* Include fast math option in quantization config
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* Fix linter warnings and review nits
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* Use TE license
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* Fix bug where kernel is always launched on stream
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* Restore BF16 intermediate downcast in fused RHT-cast kernels
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* fix numerical test of grouped kernel
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* Make sure row-wise and col-wise quantization use different RNG seeds
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Signed-off-by: Tim Moon <tmoon@nvidia.com>
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eb8e792b

05 Dec, 2025 1 commit

Fix bugs from refactoring C++ tensor class (#2481) · f0572aa5

Tim Moon authored Dec 04, 2025



Remve assumption in quantize/activation kernels that data buffer is initialized
Signed-off-by: Tim Moon <tmoon@nvidia.com>

f0572aa5

30 Oct, 2025 1 commit

[Common] Split cast/gated kernels by scaling mode (#2248) · 0e80c847

Oleg Goncharov authored Oct 30, 2025



* Separated gated and dequantize kernels
Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>

* Separated quantize, dequantize and gated functions
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* Fixed lint issues
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* Changed files description. Completely removed non-identity activations from the NVFP4 transpose test suite
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* Removed unsupported template arguments in NVFP4 quantize
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* Fixed undefined symbol error
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0e80c847