Lumpiasty/llama.cpp
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spec : add DFlash2 support (local convolution + candidate selector) (#27342) (#27816)

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* spec : add DFlash2 support (local convolution + candidate selector) (#27342)

* support DFlash2

* Add p_min in DFlash2

Assisted-by: Claude Opus 5

* Revert unnecessary changes

Assisted-by: Claude Opus 5

* Revert draft sampling in rejection sampling

Assisted-by: Claude Opus 5

* Refactor code structure

Assisted-by: Claude Opus 5

* Delete embedding scaling

Assisted-by: Claude Opus 5

* Gate output transforms on DFlash2

Assisted-by: Claude Opus 5

* Optimize Dflash 2 cost

Assisted-by: Claude Opus 5

* Avoid using atoi

Assisted-by: Claude Opus 5

* Modify comments

Assisted-by: Claude Opus 5

* Move llama_model_dflash_selector_top_k to llama-ext.h

Assisted-by: Claude Opus 5

* Formatting

Assisted-by: Claude Opus 5

* Apply patch to fix the mrope bug

Assisted-by: Claude Opus 5

* fix ci

Assisted-by: Claude Opus 5

* Fix graph number calculation

Assisted-by: Claude Opus 5

* rename hid and unary

Assisted-by: Claude Opus 5

---------

Co-authored-by: Jian Chen <jianchen0311@gmail.com>
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>

* revert top-k.cu changes

---------

Co-authored-by: Zihan Zhang <tiancaizhangdaxian@sjtu.edu.cn>
Co-authored-by: Jian Chen <jianchen0311@gmail.com>
This commit is contained in:
Xuan-Son Nguyen
2026-08-27 19:17:07 +02:00
committed by GitHub
co-authored by Jian Chen Zihan Zhang
parent 58546250cf
commit b10f9ca58c
15 changed files with 538 additions and 24 deletions
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src/llama-context.cpp
+4
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@@ -2307,6 +2307,10 @@ uint32_t llama_context::graph_max_nodes(uint32_t n_tokens) const {
model.arch == LLM_ARCH_MINIMAX_01 ||
model.arch == LLM_ARCH_MINIMAX_M3) {
res = std::max<uint32_t>(n_tokens * 40, 32u * model.n_tensors());
} else if (model.arch == LLM_ARCH_DFLASH && model.hparams.dflash_selector_rank > 0) {
// DFlash2's convolutions and selector are shape work rather than matmuls,
// so they cost ~8.6 nodes per tensor against ~5.9 for a plain DFlash draft
res = std::max<uint32_t>(1024u, 12u*model.n_tensors());
} else {
res = std::max<uint32_t>(1024u, 8u*model.n_tensors());
for (const auto & lora : model.loras) {