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* Test case to reproduce the init error
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* Fixed rowwise dbias error
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* Changed ptx API
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* Minor corrections
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* Fixes per code review
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* Minor refactoring
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* Modified mismatches checks of MXFP8 to address FP8 numerics
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Signed-off-by: Oleg Goncharov <ogoncharov@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Added support of FP4 data type
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* Refactoring to BitsNum in progress
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* Make pytorch changes
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* inline funcs
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* fix cpp warning
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* more fix
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---------
Signed-off-by: Xin Yao <xiny@nvidia.com>

* 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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* Fix merge conflict with name change.
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* Change API to use two scaling mode enums.
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* Fix typo.
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* Update some call sites.
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* Save memory by dropping reference to saved tensors.

Issues previously observed are solved.
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* Merge conflict from rebase.
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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.

Hardcodes the default values.
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* Lint changes.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* 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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* Copyright and header guard.
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* Updating torch dispatch code.
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Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* 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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---------
Signed-off-by: Keith Wyss <kwyss@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Tim Moon <tmoon@nvidia.com>
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Signed-off-by: Przemek Tredak <ptredak@nvidia.com>