Lumpiasty/llama.cpp
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dflash: pass missing NVFP4 scales to attention operations (#28000)

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- DFlash2 NVFP4 draft models produced almost no accepted speculative
tokens because the Q, K, V, and output projection scales were not
passed to the corresponding graph operations.
This commit is contained in:
JamePeng
2026-08-30 11:34:39 +03:00
committed by GitHub
parent bebc9350ec
commit cc231cb0da
1 changed files with 7 additions and 7 deletions
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src/models/dflash.cpp
+7 -7
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@@ -615,8 +615,8 @@ llama_model_dflash::graph<false>::graph(const llama_model & model, const llm_gra
for (int il = 0; il < n_layer; ++il) { for (int il = 0; il < n_layer; ++il) {
const auto & layer = model.layers[il]; const auto & layer = model.layers[il];
ggml_tensor * Kcur = build_lora_mm(layer.wk, inp_g); ggml_tensor * Kcur = build_lora_mm(layer.wk, inp_g, layer.wk_s);
ggml_tensor * Vcur = build_lora_mm(layer.wv, inp_g); ggml_tensor * Vcur = build_lora_mm(layer.wv, inp_g, layer.wv_s);
Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens); Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
Vcur = ggml_reshape_3d(ctx0, Vcur, n_embd_head, n_head_kv, n_tokens); Vcur = ggml_reshape_3d(ctx0, Vcur, n_embd_head, n_head_kv, n_tokens);
@@ -698,9 +698,9 @@ llama_model_dflash::graph<false>::graph(const llama_model & model, const llm_gra
cb(noise_norm, "attn_conv_in", il); cb(noise_norm, "attn_conv_in", il);
} }
ggml_tensor * Qcur = build_lora_mm(layer.wq, noise_norm); ggml_tensor * Qcur = build_lora_mm(layer.wq, noise_norm, layer.wq_s);
ggml_tensor * Kcur = build_lora_mm(layer.wk, noise_norm); ggml_tensor * Kcur = build_lora_mm(layer.wk, noise_norm, layer.wk_s);
ggml_tensor * Vcur = build_lora_mm(layer.wv, noise_norm); ggml_tensor * Vcur = build_lora_mm(layer.wv, noise_norm, layer.wv_s);
Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens); Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens); Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
@@ -717,8 +717,8 @@ llama_model_dflash::graph<false>::graph(const llama_model & model, const llm_gra
// cache-aware, non-causal attention // cache-aware, non-causal attention
ggml_tensor * cur = use_iswa ggml_tensor * cur = use_iswa
? build_attn(inp_attn_iswa, layer.wo, NULL, NULL, Qcur, Kcur, Vcur, nullptr, layer.attn_sinks, nullptr, kq_scale, il) ? build_attn(inp_attn_iswa, layer.wo, NULL, layer.wo_s, Qcur, Kcur, Vcur, nullptr, layer.attn_sinks, nullptr, kq_scale, il)
: build_attn(inp_attn, layer.wo, NULL, NULL, Qcur, Kcur, Vcur, nullptr, layer.attn_sinks, nullptr, kq_scale, il); : build_attn(inp_attn, layer.wo, NULL, layer.wo_s, Qcur, Kcur, Vcur, nullptr, layer.attn_sinks, nullptr, kq_scale, il);
if (attn_dynamic) { if (attn_dynamic) {
cur = build_dflash2_conv(*this, cur, attn_dynamic, layer.dflash_attn_conv_base, 1); cur = build_dflash2_conv(*this, cur, attn_dynamic, layer.dflash_attn_conv_base, 1);