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fix(dflash): derive n_target_layers fallback in gguf_draft_loader #138

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Merged
davide221 merged 2 commits into from
May 12, 2026
+52 −24
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fix(dflash): derive n_target_layers fallback in gguf_draft_loader #138

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ce5e8dc
fix(dflash): derive n_target_layers fallback in gguf_draft_loader
javierpazo May 9, 2026
da04f6f
Merge remote-tracking branch 'origin/main' into xabicasa/dflash-gguf-…
davide221 May 12, 2026
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76 changes: 52 additions & 24 deletions dflash/src/draft/draft_gguf_loader.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -6,12 +6,10 @@
// types — ggml's ggml_mul_mat handles Q8_0 × F32 dequantization transparently.
//
// GGUF arch: "qwen35-dflash-draft" (from convert_dflash_to_gguf.py /
// quantize_draft_q8.py) or the newer "dflash-draft" export. Tensor naming
// convention:
// quantize_draft_q8.py). Tensor naming convention:
//
// dflash.fc.weight / dflash_fc.weight [5*hidden, hidden] Q8_0 / F16
// dflash.hidden_norm.weight /
// dflash_hidden_norm.weight [hidden] F32
// dflash.fc.weight [5*hidden, hidden] Q8_0 / F16
// dflash.hidden_norm.weight [hidden] F32
// output_norm.weight [hidden] F32
// blk.<i>.attn_norm.weight [hidden] F32
// blk.<i>.ffn_norm.weight [hidden] F32
Expand Down Expand Up @@ -108,6 +106,14 @@ uint32_t get_u32_or(const gguf_context * g, const char * key, uint32_t fallback)
return gguf_get_val_u32(g, id);
}

int count_swa_layers(const DraftWeights & w) {
int n_swa = 0;
for (const DraftLayer & layer : w.layers) {
if (layer.is_swa) n_swa++;
}
return n_swa;
}

} // namespace

bool load_draft_gguf(const std::string & path,
Expand All @@ -126,6 +132,7 @@ bool load_draft_gguf(const std::string & path,
}

// Validate arch
std::string arch_s;
{
int64_t arch_id = gguf_find_key(gctx, "general.architecture");
if (arch_id < 0) {
Expand All @@ -134,8 +141,8 @@ bool load_draft_gguf(const std::string & path,
return false;
}
const char * arch = gguf_get_val_str(gctx, arch_id);
if (std::string(arch) != "qwen35-dflash-draft" &&
std::string(arch) != "dflash-draft") {
arch_s = arch;
if (arch_s != "qwen35-dflash-draft" && arch_s != "dflash-draft") {
set_last_error(std::string("unexpected draft arch: ") + arch +
" (expected qwen35-dflash-draft or dflash-draft)");
gguf_free(gctx);
Expand All @@ -144,8 +151,7 @@ bool load_draft_gguf(const std::string & path,
}

// Read dimensions from GGUF metadata
int64_t arch_id = gguf_find_key(gctx, "general.architecture");
const char * A = gguf_get_val_str(gctx, arch_id);
const char * A = arch_s.c_str();
char key[128];

auto read_u32 = [&](const char * suffix, uint32_t fallback) -> uint32_t {
Expand All @@ -162,16 +168,17 @@ bool load_draft_gguf(const std::string & path,
const uint32_t block_sz = read_u32("dflash.block_size", 0);
uint32_t n_tgt_lay = read_u32("dflash.n_target_layers", 0);
if (n_tgt_lay == 0) {
const uint32_t n_tgt_feat = read_u32("dflash.n_target_features", 0);
if (n_tgt_feat != 0 && n_embd != 0 && (n_tgt_feat % n_embd) == 0) {
n_tgt_lay = n_tgt_feat / n_embd;
std::snprintf(key, sizeof(key), "%s.%s", A, "dflash.target_layer_ids");
const int64_t target_ids_id = gguf_find_key(gctx, key);
if (target_ids_id >= 0 &&
gguf_get_kv_type(gctx, target_ids_id) == GGUF_TYPE_ARRAY) {
n_tgt_lay = (uint32_t)gguf_get_arr_n(gctx, target_ids_id);
}
}
if (n_tgt_lay == 0) {
std::snprintf(key, sizeof(key), "%s.%s", A, "dflash.target_layer_ids");
int64_t id = gguf_find_key(gctx, key);
if (id >= 0) {
n_tgt_lay = (uint32_t)gguf_get_arr_n(gctx, id);
if (n_tgt_lay == 0 && n_embd != 0) {
const uint32_t n_target_features = read_u32("dflash.n_target_features", 0);
if (n_target_features != 0 && (n_target_features % n_embd) == 0) {
n_tgt_lay = n_target_features / n_embd;
}
}

Expand Down Expand Up @@ -240,17 +247,17 @@ bool load_draft_gguf(const std::string & path,
auto g = [&](const char * name) -> ggml_tensor * {
return ggml_get_tensor(meta_ctx, name);
};

auto first = [](ggml_tensor * a, ggml_tensor * b) -> ggml_tensor * {
return a ? a : b;
auto g_any = [&](const char * a, const char * b) -> ggml_tensor * {
if (ggml_tensor * t = g(a)) return t;
return g(b);
};

out.fc = first(g("dflash.fc.weight"), g("dflash_fc.weight"));
out.hidden_norm = first(g("dflash.hidden_norm.weight"), g("dflash_hidden_norm.weight"));
out.fc = g_any("dflash.fc.weight", "dflash_fc.weight");
out.hidden_norm = g_any("dflash.hidden_norm.weight", "dflash_hidden_norm.weight");
out.out_norm = g("output_norm.weight");
if (!out.fc || !out.hidden_norm || !out.out_norm) {
set_last_error("draft GGUF: missing top-level tensors "
"(dflash fc / dflash hidden norm / output_norm)");
"(dflash.fc|dflash_fc / dflash.hidden_norm|dflash_hidden_norm / output_norm)");
gguf_free(gctx);
return false;
}
Expand All @@ -263,7 +270,8 @@ bool load_draft_gguf(const std::string & path,
};
DraftLayer & L = out.layers[il];
L.attn_norm = fnd("attn_norm.weight");
L.ffn_norm = first(fnd("ffn_norm.weight"), fnd("post_attention_norm.weight"));
L.ffn_norm = fnd("ffn_norm.weight");
if (!L.ffn_norm) L.ffn_norm = fnd("post_attention_norm.weight");
L.wq = fnd("attn_q.weight");
L.wk = fnd("attn_k.weight");
L.wv = fnd("attn_v.weight");
Expand All @@ -283,6 +291,26 @@ bool load_draft_gguf(const std::string & path,
}
}

// GGUF Qwen3.6 drafters carry SWA metadata emitted by the converter:
// dflash-draft.attention.sliding_window = 2048
// dflash-draft.attention.sliding_window_pattern = [true,true,true,true,false]
out.swa_window = (int)read_u32("attention.sliding_window", 0);
std::snprintf(key, sizeof(key), "%s.%s", A, "attention.sliding_window_pattern");
int64_t swp_id = gguf_find_key(gctx, key);
if (swp_id >= 0 && gguf_get_kv_type(gctx, swp_id) == GGUF_TYPE_ARRAY &&
gguf_get_arr_type(gctx, swp_id) == GGUF_TYPE_BOOL) {
const size_t n = gguf_get_arr_n(gctx, swp_id);
const bool * pattern = static_cast<const bool *>(gguf_get_arr_data(gctx, swp_id));
for (size_t il = 0; il < n && il < out.layers.size(); il++) {
out.layers[il].is_swa = pattern[il];
}
}
const int n_swa = count_swa_layers(out);
if (n_swa > 0) {
std::fprintf(stderr, "[draft GGUF] SWA layers: %d/%d (window=%d)\n",
n_swa, out.n_layer, out.swa_window);
}

// ── 3. Allocate CUDA buffer for all tensors ──────────────────────────
out.buf = ggml_backend_alloc_ctx_tensors(meta_ctx, backend);
if (!out.buf) {
Expand Down