b11800

llama: create new fused op for QSA mask (#30640)

• llama: create new fused op for QSA scoring

• enroll glm5.3-next too

• tests : initialize the remaining tensors in test_kpool_mask

The harness sentinels were left uninitialized, so leftover memory could read as NaN and fail the NaN check.

• ggml: generalize the k-pool mask op into ggml_top_k_mask

The k-pool mask op only covered the pooled QSA selection of qwen4exp
and glm5-next, while the DSA models and the DeepSeek V4 CSA build the
same top-k mask by hand with fill, set_rows and add.

ggml_top_k_mask(mask, top_k, score, blocks, extra) keeps the mask
cells of the live picks and the extra cells, and sets the rest to
-inf. Every row tensor is 4D in the layout of top_k, and the mask is
broadcast to those rows, so a selection can also be made per head.
score, blocks and extra are optional: without score every pick is
live, without blocks a pick is a cell, and extra holds the cells a
row keeps without a pick.

llm_graph_context::build_fused_top_k_mask views the row tensors in
the layout of kq_mask and registers the fused node. The k-pool
models, the DSA attention of build_attn and the DeepSeek V4 CSA mask
use it when the probe enables the op, and keep their current path on
backends without it.

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Co-authored-by: Pascal admin@serveurperso.com

Website:

• https://llama.app

Attestations:

• https://github.com/ggml-org/llama.cpp/attestations/58392496

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