feat(laguna): add Domino GRU draft head#443
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1 issue found across 11 files
Prompt for AI agents (unresolved issues)
Check if these issues are valid — if so, understand the root cause of each and fix them. If appropriate, use sub-agents to investigate and fix each issue separately.
<file name="server/src/draft/draft_gguf_loader.cpp">
<violation number="1" location="server/src/draft/draft_gguf_loader.cpp:119">
P2: Domino 1D shape validation is incomplete: it only checks `ne[0]` and does not enforce that higher dimensions are 1, so malformed non-vector tensors can pass loader validation.</violation>
</file>
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Re-trigger cubic
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| bool check_shape_1d(const ggml_tensor * t, int64_t ne0, const char * name, char * buf, size_t buf_sz) { | ||
| if (!t || t->ne[0] != ne0) { |
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P2: Domino 1D shape validation is incomplete: it only checks ne[0] and does not enforce that higher dimensions are 1, so malformed non-vector tensors can pass loader validation.
Prompt for AI agents
Check if this issue is valid — if so, understand the root cause and fix it. At server/src/draft/draft_gguf_loader.cpp, line 119:
<comment>Domino 1D shape validation is incomplete: it only checks `ne[0]` and does not enforce that higher dimensions are 1, so malformed non-vector tensors can pass loader validation.</comment>
<file context>
@@ -115,6 +115,29 @@ int count_swa_layers(const DraftWeights & w) {
}
+bool check_shape_1d(const ggml_tensor * t, int64_t ne0, const char * name, char * buf, size_t buf_sz) {
+ if (!t || t->ne[0] != ne0) {
+ std::snprintf(buf, buf_sz, "draft GGUF: Domino tensor %s shape mismatch: got [%lld], expected [%lld]",
+ name, t ? (long long)t->ne[0] : -1LL, (long long)ne0);
</file context>
Suggested change
| if (!t || t->ne[0] != ne0) { | |
| if (!t || t->ne[0] != ne0 || t->ne[1] != 1 || t->ne[2] != 1 || t->ne[3] != 1) { |
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Summary
Bench notes
Ran the 30-case he,gsm,math harness on lucebox-ts RTX 3090 with Laguna-XS.2 target, max_ctx 4096, default cache, no DDTree.
v13-final+Domino:
Compared with v12, v13-final+Domino is slower but improves GSM by one case. This PR is the runtime/model-loading support, not a claim that v13 is the best drafter.
Checks
Note: a fresh clean-worktree CUDA rebuild on the 3090 was attempted, but the full llama.cpp CUDA dependency compile was killed with Error 137 under memory pressure before reaching the project-only compile.