refactor(prefetch): clean up unused variables, dead functions, and hardcoded paths

c/olmoe.c

@@ -89,13 +89,8 @@ static volatile unsigned pilot_r = 0, pilot_w = 0;
 static Model *pilot_m = NULL;
 static int g_pilot = 0;
 static int g_wide  = 1;  /* IMPROVEMENT 4: top-K * g_wide candidates prefetched */
-static volatile int g_curr_layer = 0; /* current layer processed by the main thread */
-static const int g_asymmetric_caps[16] = {
-    34, 36, 34, 34, 28, 30, 26, 28, 34, 34, 34, 34, 34, 36, 30, 30
-};
 
 static void pilot_prefetch(Model *m, int lnext, const float *x, int S);
-static void pilot_prefetch_next_token(Model *m, int lnext);
 static void *pilot_worker(void *arg);
 static void ensure_pilot_worker_started(Model *m);
 static void slot_ensure_allocated(Model *m, Slot *s);
@@ -832,64 +827,6 @@ static void pilot_prefetch(Model *m, int lnext, const float *x, int S) {
     free(logits);
 }
 
-static void pilot_prefetch_next_token(Model *m, int lnext) {
-    if (lnext < 0 || lnext >= m->c.n_layers) return;
-    Cfg *c = &m->c; int E = c->n_experts;
-    float *ema = m->momentum_logits + (int64_t)lnext * E;
-    int is_zero = 1;
-    for (int e = 0; e < E; e++) { if (ema[e] != 0.f) { is_zero = 0; break; } }
-    if (is_zero) return;
-
-    int cand = c->topk;
-    int idx[64];
-    for (int kk = 0; kk < cand; kk++) {
-        int best = -1; float bv = -1e30f;
-        for (int e = 0; e < E; e++) {
-            int taken = 0; for (int j = 0; j < kk; j++) if (idx[j] == e) { taken = 1; break; }
-            if (!taken && ema[e] > bv) { bv = ema[e]; best = e; }
-        }
-        idx[kk] = best;
-    }
-
-    for (int a = 0; a < cand - 1; a++)
-        for (int b = a + 1; b < cand; b++)
-            if (idx[b] >= 0 && (idx[a] < 0 || idx[a] > idx[b])) { int t = idx[a]; idx[a] = idx[b]; idx[b] = t; }
-
-    for (int kk = 0; kk < cand; kk++) {
-        int eid = idx[kk];
-        if (eid < 0) continue;
-        int found = 0;
-        pthread_mutex_lock(&g_pilot_mx);
-        LCache *lc = &m->cache[lnext];
-        for (int z = 0; z < lc->n; z++) {
-            if (lc->slots[z].eid == eid) { found = 1; break; }
-        }
-        pthread_mutex_unlock(&g_pilot_mx);
-        if (!found) {
-            int gidx = lnext * E + eid;
-            pthread_mutex_lock(&g_pilot_mx);
-            int already_queued = m->is_queued[gidx];
-            if (!already_queued) {
-                m->is_queued[gidx] = 1;
-            }
-            pthread_mutex_unlock(&g_pilot_mx);
-
-            if (!already_queued) {
-                unsigned w2 = __atomic_load_n(&pilot_w, __ATOMIC_RELAXED);
-                unsigned r2 = __atomic_load_n(&pilot_r, __ATOMIC_ACQUIRE);
-                if (w2 - r2 < 4096) {
-                    pilot_q[w2 & 4095].l = lnext;
-                    pilot_q[w2 & 4095].e = eid;
-                    __atomic_store_n(&pilot_w, w2 + 1, __ATOMIC_RELEASE);
-                } else {
-                    pthread_mutex_lock(&g_pilot_mx);
-                    m->is_queued[gidx] = 0;
-                    pthread_mutex_unlock(&g_pilot_mx);
-                }
-            }
-        }
-    }
-}
 
 /* generazione greedy. prompt[np] -> riempie out[np+n_new] */
 static void generate(Model *m, const int *prompt, int np, int n_new, int *out) {

c/tools/make_olmoe_real_oracle.py

@@ -22,29 +22,25 @@ try:
 except ImportError as exc:
     sys.exit(f"Missing deps: {exc}. Run: pip install torch transformers")
 
-MODEL_DIR = (
+MODEL_ID = "allenai/OLMoE-1B-7B-0125-Instruct"
-    Path(r"C:\Users\egonr\.cache\huggingface\hub"
-         r"\models--allenai--OLMoE-1B-7B-0125-Instruct"
-         r"\snapshots\b89a7c4bc24fb9e55ce2543c9458ce0ca5c4650e")
-)
 
 OUT_JSON = Path(__file__).resolve().parent.parent / "ref_olmoe_real.json"
 
 PROMPT = "The capital of France is"
 MAX_NEW_TOKENS = 12
 
-print(f"Loading tokenizer from {MODEL_DIR} ...")
+print(f"Loading tokenizer from {MODEL_ID} ...")
-tokenizer = AutoTokenizer.from_pretrained(str(MODEL_DIR))
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
 
 print("Encoding prompt ...")
 enc = tokenizer(PROMPT, return_tensors="pt")
 prompt_ids = enc["input_ids"][0].tolist()
 print(f"  Prompt IDs ({len(prompt_ids)}): {prompt_ids}")
 
-print(f"Loading OLMoE model from {MODEL_DIR} ...")
+print(f"Loading OLMoE model from {MODEL_ID} ...")
 print("  (this will use ~14 GB RAM — please be patient)")
 model = OlmoeForCausalLM.from_pretrained(
-    str(MODEL_DIR),
+    MODEL_ID,
     torch_dtype=torch.bfloat16,
     device_map="cpu",
     low_cpu_mem_usage=True,

c/tools/test_olmoe_real.py

@@ -22,8 +22,9 @@ if sys.platform == "win32":
             pass
 
 HERE = Path(__file__).resolve().parent.parent
-ENGINE = HERE / "olmoe.exe"
+ext = ".exe" if sys.platform == "win32" else ""
-SNAP = HERE / "olmoe_i4"
+ENGINE = HERE / f"olmoe{ext}"
+SNAP = os.getenv("SNAP", str(HERE.parent / "olmoe_merged"))
 REF_OUT = HERE / "ref_olmoe_real.json"
 BOOTSTRAP_REF = HERE / "ref_olmoe_bootstrap.json"