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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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* Change API name.
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* Fix merge conflict with name change.
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* Use common tensor map API.
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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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* Tests for torch tensor API surface.

Since the quantized tensor is a tensor
subclass, these tests exercise torch hooks.
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* Reuse scale calculation between quantizer refs.
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* Save memory by dropping reference to saved tensors.

Issues previously observed are solved.
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* 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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* 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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* Fix exception type.
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* Use TypeInfo
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* MR feedback.
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* Update JAX scaling mode enum
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* Skip tests on Lovelace
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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>

* Ignore IDE files
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Fix typing errors
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Ignore devcontainer files
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Avoid import from private module
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

* Apply @timmoon10 's suggestions
Signed-off-by: Jan Bielak <jbielak@nvidia.com>

---------
Signed-off-by: Jan Bielak <jbielak@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>

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

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