GitLab

[PyTorch] fix input_quantizer usage for save_original_input; fix blockwise FP8 convert_and_update_tensor (#1978)

* fix input_quantizer in save_original_input bwd
Signed-off-by: Hongxiao Bai <hongxiaob@nvidia.com>

* fix get shape of blockwise tensor with only compact colwise data
Signed-off-by: Hongxiao Bai <hongxiaob@nvidia.com>

* fix blockwise FP8 convert_and_update_tensor
Signed-off-by: Hongxiao Bai <hongxiaob@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



---------
Signed-off-by: Hongxiao Bai <hongxiaob@nvidia.com>
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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

[PyTorch] FP8 Subchannel Recipe With FP8 Gather And Configurable Scaling Factor Tensor Swizzling (#1707)

* functional kernel for columnwise + no-transpose option, still hacky
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* pass all quantizer unit tests
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* refactor, add gemm ready api
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* make format options private members, simplify api
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* swizzle scales right before gemm
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* bug fix of single layer test
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* attempt to fix lint issue
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fp8 gather pass, need minor refine
Signed-off-by: zhongboz <zhongboz@nvidia.com>

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* fix return_layernorm_output_gathered case
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* remove special cases, add sanity check before gemm
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* fix lint
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* lint ungrouped imports
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



* Implement dequantize for compact 1D blocks.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* add more unit test with dequantize compact supported
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* lint again
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* make ag for subchannel respect async
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* zero tolerance in distributed test
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* fix zero tolerance test
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* resolve rebase issues
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* lint & format
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* fix lint
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* clean up
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* bug fix
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* relax rtol for fp32 distributed test
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* fix some ci issue
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* fix ci test failure in debug mode
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* Force row-wise and column-wise data to have same data format

Prototype "all-gather usage" in quantizer.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Remove dead logic for high-precision AGs
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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* Debug FP8 block-wise tensor tests
Signed-off-by: Tim Moon <tmoon@nvidia.com>

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

* Handle case where LayerNormLinear returns gathered norm output
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* fix debug mode
Signed-off-by: zhongboz <zhongboz@nvidia.com>

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Signed-off-by: Keith Wyss <kwyss@nvidia.com>
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* Add fp8_primary_weights support for blockwise scaling
Signed-off-by: kunlunl <kunlunl@nvidia.com>

custom fsdp
Signed-off-by: kunlunl <kunlunl@nvidia.com>

[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



Add view to blockwise fp8 tensor
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* Fix columnwise_shape in backward of view()
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* Add comments to the unit of start_offset
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* Add test for view and reshape for blockwise fp8 tensor
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* Add implementation for self._columnwise_scale_inv is not existed
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



* Track down checks for _columnwise_data is None and adding checks for  _columnwise_invalid
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



* Add assertion to check whether ._quantizer is None
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* rename partial_cast.cu -> fp8_block_scaling_partial_cast.cu
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* rename partial_cast kernel to fp8_block_scaling_partial_cast kernel
Signed-off-by: kunlunl <kunlunl@nvidia.com>

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for more information, see https://pre-commit.ci



* Add shfl_sync in partial cast kernel
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* Remove columnwise_invalid flag
Signed-off-by: kunlunl <kunlunl@nvidia.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci



* Add comments about out-of-bounds write
Signed-off-by: kunlunl <kunlunl@nvidia.com>

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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* 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.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* 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.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Recipe setup for Linear modules.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* 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.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update full recompute feature to save recipe.

The recompute context uses the same recipe
and fp8 settings as the original fwd pass.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR Feedback. Avoid reusing quantizer objects.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update logic in module.
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* Format py.
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* Update for PP bug.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update test numerics.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update force_power_of_2 scales in the recipe.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update usage method to satisfy upstream changes.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* fix subchannel recipe in distributed test with bf16 gather
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* Edit and cleanup BF16 gather code.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update test import.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* support columnwise only mode to 1D quantize kernel
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* Format and move enum
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Skip alloc.
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* try async bf16 gather
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* Format python code.
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* Document and type code.
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* Update pytorch lint errors.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Dont set high precision dtype.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add test for sanity and CG; fix CG for sequential?
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Keep make_quantizers API stable

Update num_quantizers instead to pass cuda_graph tests.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Fix import name.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Rename recipe method.
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* Skip grouped linear sanity test.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* 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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* Disable CUDA graph.
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* Simplify layernorm linear
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* Cleanup 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

Apply MR comment change.
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* Lint fix.
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* MR feedback.
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* Enable cuda graph tests.
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* Reduce chance of spurious failure and reword.
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* Review suggestions from @timmoon10
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* Update CPP tests.
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* Update common.h
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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.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Alignment for 1D scaling for GEMM edge case.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR feedback.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Change API name.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Fix merge conflict with name change.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Use common tensor map API.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Change API to use two scaling mode enums.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Fix typo.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update some call sites.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Tests for torch tensor API surface.

Since the quantized tensor is a tensor
subclass, these tests exercise torch hooks.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Reuse scale calculation between quantizer refs.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Save memory by dropping reference to saved tensors.

Issues previously observed are solved.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Remove constexpr parameters from kernel.

Code size is reduced with fewer constexpr params.
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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
for block scaled fp8.
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* Move benchmark to te_playground
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* Remove amax_epsilon and pow_2_scales from tensor.

Hardcodes the default values.
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* Lint changes.
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* Fixup MR changes that broke.
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* Safer ifdef in kernel.
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* Documentation prose.
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* Reuse compute_scale function from Current Scaling.
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* Bugfix on inf_value scale refactor.
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* Remove qopt calls from test.
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* Update pytest list.
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* Add copyright to reference scale calc.
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* Use ptx.cuh functions instead of cde.
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* Update shape logic with allocation and reuse shape.
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* Usage defaults MR feedback.
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* Updating torch dispatch code.
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* Fix exception type.
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* Use TypeInfo
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* MR feedback.
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* Update CS scale update test to use updated ref impl
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* Update JAX scaling mode enum
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* Skip tests on Lovelace
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