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Fixes #1692
Signed-off-by: Nicolas Castet <26874160+nvcastet@users.noreply.github.com>

Introduce nvte_memset to provide a fill kernel that is faster than cudaMemsetAsync for small sizes (#1716)

* nvte_memset fills single float value
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Support larger sizes than a single value and add tests
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

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* Move radix sort to core
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* Fix; change fused_attn to include C header
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* Review comments
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* Fix args
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* add support for `sb1d` freqs tensor in Fused RoPE
Signed-off-by: Sudhakar Singh <sudhakars@nvidia.com>

* add `start_positions` variable to `apply_rotary_pos_emb` function to make staggered rope application faster
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* rtx5090 arch fix support
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* apprend `nvte` to the function name so that its visible in framework specific dirs
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* fix typo
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* add filter for nvte_is_supported_nontn_fp8_gemm
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Revert "Allow NVTEShape to own data. (#1674)"

This reverts commit e61ce77c

.
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* Allow NVTEShape to own data.
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* Convert repeated copy paths to nvte_make_shape calls.
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* Add a flag to support computing zero-centered gamma in weight dtype or compute dtype for CuDNN
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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.
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* Add GEMM logic for blockwise quantized tensors.

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* 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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* Add GEMM logic for blockwise quantized tensors.

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* Blockwise float8 quantizer and quantized tensor class.

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