GitLab

Use ocp fp8.
Workaround: test_cast_float8blockwise.cu link wrong std::max
Signed-off-by: wenjh <wenjh@sugon.com>

* Allow NVTEShape to own data.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Convert repeated copy paths to nvte_make_shape calls.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Apply suggestions from code review
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* Build fixes.
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* MR feedback.
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Repeated calls to nvte_shape should not invalidate
previous data pointers.

It would be possible to avoid unnecessary comparisons
by duplicating some of the logic from shape() so that
the cache is only relevant when columnwise shapes are
involved. Whether this code duplication is preferable
to the comparisons that arise from by value semantics
of reusing shape is a judgment call.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add GEMM logic for blockwise quantized tensors.

GEMM test cases included in pytorch integration.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update NVTE_BLOCK_SCALING for GEMM.
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* Gate feature on CUDA 12.9
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* Gemm typo.
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* Remove unecessary type converter change.
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* Reflect epilogue availability and test supported epilogues.
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* GEMM simplifications from recipe branch.
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* Format py code.
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* Update GEMM DGelu tests to match support depending on output dtype.
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* Force pow2Scales in GEMM
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* Add GEMM test to pytorch test suite.
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* Add copyright to GEMM test.
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* Update import for GEMM test.
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* Add license.
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* Update test gemm supported predicate.
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* Use sgemm like interfaces and naming.
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* Rewrite GEMM comment.
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* MR Feedback.
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* Recipe setup for Linear modules.
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* Use 12.9 feature test.
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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.

The recompute context uses the same recipe
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* MR Feedback. Avoid reusing quantizer objects.
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* Update logic in module.
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* Format py.
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* Update for PP bug.
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* Update test numerics.
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* Update force_power_of_2 scales in the recipe.
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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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* Update test import.
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* support columnwise only mode to 1D quantize kernel
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* Format and move enum
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* Update pytorch lint errors.
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* Dont set high precision dtype.
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* Add test for sanity and CG; fix CG for sequential?
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* Keep make_quantizers API stable

Update num_quantizers instead to pass cuda_graph tests.
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* Fix import name.
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* Skip grouped linear sanity test.
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* Set usage before BF16 gather.
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* refactor for nvte_quantize_v2
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* Format code.
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* Cleanup 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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* Enable cuda graph tests.
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* Reduce chance of spurious failure and reword.
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* Update test_float8blockwisetensor.py
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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.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Apply linting changes.
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* Alignment for 1D scaling for GEMM edge case.
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* MR feedback.
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* Reuse scale calculation between quantizer refs.
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* Merge conflict from rebase.
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* Add shape implementations for block scaling.

nvte_shape was added upstream. Logic added
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* Move benchmark to te_playground
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* Remove amax_epsilon and pow_2_scales from tensor.

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* Use TypeInfo
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* Skip tests on Lovelace
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

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

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

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

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

Use unsigned char for byte dtype
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Do not include logging macros in installed C headers
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug logging macros
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug C++ tests

Use Google style for header includes.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Update CUDA driver macros

Incorporating changes from #389.
Co-authored-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Jan Bielak <jbielak@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use core error checking macros in PyTorch extensions

Hack to get around macro redefinition warning.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix missing arg when getting CUDA driver error string
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Reuse logging header in frameworks
Signed-off-by: Tim Moon <tmoon@nvidia.com>

---------
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Jan Bielak <jbielak@nvidia.com>

* Initial implementation of NVRTC infrastructure
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Initial NVRTC impl for transpose

NVRTC gives compilation errors at runtime. Everything else compiles and passes tests as expected.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug NVRTC transpose impl

NVRTC kernel compiles, runs, and passes tests with FP32.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use variadic template for kernel arguments in RTC kernel launch func
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Refactoring

Added utility header for CUDA Runtime API. Optimized concat_strings function.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add helper function for regex substitutions in strings
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add option to disable NVRTC support
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add support for header includes in NVRTC kernels
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Access lazily-initialized CUDA driver lib and add option to specify CUDA header dir
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Configure NVRTC transpose kernel with simple perf model
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Revert change to tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Add prime-valued test cases
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix multiple definition error
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Optimize NVRTC transpose kernel for small data sizes
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Mention NVRTC in docs
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add unit tests for NVRTC and string utils
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Add comment in install docs about NVRTC

Review suggestion from @nouiz
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Debug perf model for RTC transpose kernel
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Remove NVRTC discussion from docs
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Require CUDA headers unless NVRTC is explicitly disabled
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use diagonal coords in transpose kernel to avoid partition camping
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use std::call_once for thread-safety
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Debug CMake error
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Remove unnecessary call_once
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Remove diagonal coordinates from transpose kernel
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Use size_t indices instead of int
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Review suggestions from @ptrendx

Check build-time CUDA include path for run-time CUDA headers. Handle case where CUDA context is initially uninitialized.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Add NVTX to TE modules
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

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

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

* Add NVTX to C API
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

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

* Add NVTX to GeGlu
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
Signed-off-by: Przemek Tredak <ptredak@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>

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